1
00:00:00,760 --> 00:00:05,320
Speaker 1: Hey, everybody, Chuck here, continuing our journey down the science trail.

2
00:00:05,960 --> 00:00:07,880
Speaker 1: Here we are with I Bleeve, Episode seven on the

3
00:00:07,880 --> 00:00:14,280
Speaker 1: list How the Scientific Method Works. Welcome to Stuff you

4
00:00:14,320 --> 00:00:22,720
Speaker 1: Should Know from HowStuffWorks dot com.

5
00:00:22,800 --> 00:00:25,720
Speaker 2: Hey, and welcome to the podcast. I'm Josh Clark. There's

6
00:00:25,800 --> 00:00:29,400
Speaker 2: Charles W. Chuck Bryant, there's Jerry Stuff you should know.

7
00:00:29,600 --> 00:00:30,320
Speaker 1: Why you grinning?

8
00:00:30,480 --> 00:00:31,319
Speaker 2: It's been a while.

9
00:00:31,520 --> 00:00:31,800
Speaker 1: I know.

10
00:00:32,400 --> 00:00:35,320
Speaker 2: It's funny, Like those words come pouring out of my mouth, didn't.

11
00:00:35,360 --> 00:00:37,400
Speaker 1: It's cool you wake up in the middle of the

12
00:00:37,440 --> 00:00:39,320
Speaker 1: night saying that and give me like slugged you in

13
00:00:39,320 --> 00:00:39,680
Speaker 1: the face.

14
00:00:39,800 --> 00:00:42,760
Speaker 2: Right, She's like, go ahead, sleep, she has to dry

15
00:00:42,800 --> 00:00:43,320
Speaker 2: my brow.

16
00:00:44,159 --> 00:00:48,280
Speaker 1: Yes, we pre recorded some for December, as we like

17
00:00:48,320 --> 00:00:49,640
Speaker 1: to do to take a little time off at the

18
00:00:49,680 --> 00:00:52,800
Speaker 1: end of the year and not explain things for a

19
00:00:52,800 --> 00:00:55,600
Speaker 1: few weeks in our real lives. It's nice, like people

20
00:00:55,640 --> 00:00:56,120
Speaker 1: ask me.

21
00:00:56,120 --> 00:00:58,560
Speaker 2: Things like what happened to that stick of butter?

22
00:00:58,720 --> 00:01:00,000
Speaker 1: Yeah, I don't know, don't act.

23
00:01:00,120 --> 00:01:00,960
Speaker 2: Don't even ask me.

24
00:01:01,200 --> 00:01:03,920
Speaker 1: I could tell you, yeah, but I'm not gonna exactly.

25
00:01:03,960 --> 00:01:07,880
Speaker 1: That's how it goes in my house. Find your own butter, right,

26
00:01:08,080 --> 00:01:09,680
Speaker 1: December was find your Own Butter month.

27
00:01:09,760 --> 00:01:12,520
Speaker 2: Yeah, that's a good's that's a good one.

28
00:01:12,680 --> 00:01:14,479
Speaker 1: That should be a T shirt. Yes, stuff you should

29
00:01:14,520 --> 00:01:15,640
Speaker 1: know find your own butter.

30
00:01:16,240 --> 00:01:18,720
Speaker 2: Or December is find your own Butter month. Yeah that's right.

31
00:01:18,840 --> 00:01:21,880
Speaker 2: Maybe a stick of butter is some Garland on it. Yeah,

32
00:01:22,080 --> 00:01:22,560
Speaker 2: I like that.

33
00:01:22,920 --> 00:01:24,800
Speaker 1: So, uh, it's good to see you again, man, Good

34
00:01:24,800 --> 00:01:25,520
Speaker 1: to be back in here.

35
00:01:25,600 --> 00:01:27,720
Speaker 2: Yeah, it is nice to be back because as much as.

36
00:01:27,640 --> 00:01:30,360
Speaker 1: The break was great, I'm happy to be explaining things again.

37
00:01:30,480 --> 00:01:32,720
Speaker 2: Well that's good because if we got in here and

38
00:01:32,760 --> 00:01:34,680
Speaker 2: you're like, I can't do this, I can't do it again.

39
00:01:34,560 --> 00:01:35,240
Speaker 1: We'd be in trouble.

40
00:01:35,319 --> 00:01:37,800
Speaker 2: Yeah. Yeah, So I'm glad we're all feeling good. Jerry,

41
00:01:37,840 --> 00:01:40,679
Speaker 2: you feeling good. Jerry's got two thumbs up in a

42
00:01:40,720 --> 00:01:42,800
Speaker 2: big goofy smile, two of.

43
00:01:42,760 --> 00:01:43,520
Speaker 1: Her three thumbs.

44
00:01:44,040 --> 00:01:48,480
Speaker 2: She looks like Bob from that male enhancement pill add Oh.

45
00:01:48,560 --> 00:01:50,840
Speaker 1: See the guy, the old man that's like super buff.

46
00:01:51,880 --> 00:01:53,920
Speaker 2: I would call him old. He was middle aged. He

47
00:01:54,000 --> 00:01:56,760
Speaker 2: looked like kind of a Bob Dobbs type of dude.

48
00:01:56,840 --> 00:01:58,600
Speaker 2: I think that's kind of who he was modeled to.

49
00:01:58,640 --> 00:02:01,240
Speaker 1: See the guy that's super muscling. Now, I'm thinking of

50
00:02:01,320 --> 00:02:01,840
Speaker 1: someone different.

51
00:02:01,920 --> 00:02:03,760
Speaker 2: I think are you're thinking of Jack Llane.

52
00:02:04,000 --> 00:02:05,880
Speaker 1: No, no, no, no, just there's some ad. There's some

53
00:02:05,920 --> 00:02:08,040
Speaker 1: old man that looks like really creepy because from the

54
00:02:08,080 --> 00:02:10,600
Speaker 1: next time super like buff he looks like a twenty

55
00:02:10,600 --> 00:02:11,600
Speaker 1: five year old. No.

56
00:02:11,720 --> 00:02:14,359
Speaker 2: Remember, there was like a mail enhancement pill and I'm

57
00:02:14,360 --> 00:02:15,720
Speaker 2: making air quotes here.

58
00:02:15,800 --> 00:02:16,960
Speaker 1: For a rectalle dysfunction.

59
00:02:17,280 --> 00:02:20,440
Speaker 2: Oh well, there go the air quotes. But yes, And

60
00:02:20,480 --> 00:02:23,560
Speaker 2: it was like in the early two thousands. I think,

61
00:02:23,760 --> 00:02:26,880
Speaker 2: uh huh, maybe late nineties, but I think early two thousands,

62
00:02:26,919 --> 00:02:29,760
Speaker 2: and these ads were everywhere, and there was Bob and

63
00:02:29,840 --> 00:02:32,120
Speaker 2: like all these great things happened to him because he

64
00:02:32,280 --> 00:02:34,440
Speaker 2: started taking this pill. I can't remember the name of

65
00:02:34,480 --> 00:02:37,440
Speaker 2: the pill. But the company got into a lot of

66
00:02:37,480 --> 00:02:41,160
Speaker 2: trouble because it was basically like a subscription service and

67
00:02:41,240 --> 00:02:42,840
Speaker 2: like you gave him your credit card and you got

68
00:02:42,840 --> 00:02:45,360
Speaker 2: this free trial, but then they started sending it to

69
00:02:45,400 --> 00:02:47,800
Speaker 2: you and it was like next to impossible to cut

70
00:02:47,840 --> 00:02:48,520
Speaker 2: off service.

71
00:02:49,080 --> 00:02:49,640
Speaker 1: Interesting.

72
00:02:49,880 --> 00:02:52,120
Speaker 2: They were like, no, we want your mailness to be enhanced.

73
00:02:53,280 --> 00:02:55,679
Speaker 2: So you've seen these ads.

74
00:02:55,720 --> 00:02:59,000
Speaker 1: Yeah, I was gonna start asking questions, but why bother.

75
00:02:59,160 --> 00:03:02,040
Speaker 2: I will a YouTube. I will find it on YouTube.

76
00:03:02,080 --> 00:03:05,359
Speaker 2: I'll be like, oh, Bob, yeah you will, You'll go oh,

77
00:03:05,520 --> 00:03:07,120
Speaker 2: I won't have to come back in and record an

78
00:03:07,160 --> 00:03:08,000
Speaker 2: insert right.

79
00:03:07,880 --> 00:03:09,320
Speaker 1: The guy that's in the back of all those pill

80
00:03:09,360 --> 00:03:12,959
Speaker 1: bottles in my bathroom, so chuck.

81
00:03:13,200 --> 00:03:15,920
Speaker 2: Yes, I don't even remember how we got Oh yeah,

82
00:03:16,040 --> 00:03:19,160
Speaker 2: Jerry did that. That was Jerry's fault. But you remember

83
00:03:19,200 --> 00:03:23,480
Speaker 2: we did the Enlightenment episode. Yeah, okay, we talked a

84
00:03:23,480 --> 00:03:28,280
Speaker 2: lot about how there's this kind of tug of war

85
00:03:28,919 --> 00:03:34,920
Speaker 2: over the human psyche, sure, between rationalism and mysticism. I

86
00:03:34,920 --> 00:03:37,800
Speaker 2: guess you could you could put it. Yeah, well, I

87
00:03:37,840 --> 00:03:40,320
Speaker 2: feel like we're talking today about the scientific method.

88
00:03:40,400 --> 00:03:41,480
Speaker 1: Yeah, great idea.

89
00:03:41,520 --> 00:03:43,520
Speaker 2: By the way, thank you very much. It's been a

90
00:03:43,520 --> 00:03:48,160
Speaker 2: long time coming. Yeah, because I realized, like I don't

91
00:03:48,240 --> 00:03:50,800
Speaker 2: understand it as fully as I don't understand science. I

92
00:03:50,920 --> 00:03:53,440
Speaker 2: understand the scientific method because it's pretty cut and dry

93
00:03:53,480 --> 00:03:56,440
Speaker 2: and it's beautiful and elegant and simple. But then you

94
00:03:56,600 --> 00:03:59,680
Speaker 2: just take this thing and it came out of the

95
00:03:59,720 --> 00:04:02,240
Speaker 2: birth rationalism. Yeah, and when you place it into the

96
00:04:02,240 --> 00:04:06,600
Speaker 2: world and make it function, there's a lot of implications. Yeah,

97
00:04:06,720 --> 00:04:09,560
Speaker 2: is it being used properly? Is it being used responsibly?

98
00:04:09,680 --> 00:04:13,280
Speaker 2: Like are we putting what constitutes faith into that? You know,

99
00:04:13,360 --> 00:04:15,680
Speaker 2: like it just raises all this other stuff, and it

100
00:04:15,720 --> 00:04:18,840
Speaker 2: made me realize, like I don't understand science as much

101
00:04:18,880 --> 00:04:21,280
Speaker 2: as I want to, So researching this it was awesome.

102
00:04:21,640 --> 00:04:24,160
Speaker 1: Yeah, and this is a cool episode, I think, because

103
00:04:24,240 --> 00:04:26,400
Speaker 1: not only are we going to talk about the scientific method,

104
00:04:26,440 --> 00:04:28,920
Speaker 1: but we're going to talk about just science, like what

105
00:04:29,000 --> 00:04:32,560
Speaker 1: is science in general? And some of the rock stars

106
00:04:32,720 --> 00:04:35,839
Speaker 1: along the way who really you know, laid out the

107
00:04:35,880 --> 00:04:40,919
Speaker 1: path remarkably and like many many years ago, right like

108
00:04:40,960 --> 00:04:44,160
Speaker 1: coming up with these amazing discoveries that still like hold

109
00:04:44,800 --> 00:04:46,560
Speaker 1: you know, you can like hold their feet to the

110
00:04:46,600 --> 00:04:47,880
Speaker 1: fire for a lot of this stuff.

111
00:04:48,000 --> 00:04:52,600
Speaker 2: Yeah, because if you come upon a universal truth, yeah,

112
00:04:52,760 --> 00:04:54,599
Speaker 2: you know it is what it is, like you got

113
00:04:54,600 --> 00:04:56,840
Speaker 2: to be the person who discovered it because you know,

114
00:04:56,960 --> 00:04:59,880
Speaker 2: you saw it, you realized it a certain way. But

115
00:05:00,360 --> 00:05:01,679
Speaker 2: ultimately he was there already.

116
00:05:01,800 --> 00:05:03,839
Speaker 1: Yeah, like Newton. I mean, we'll talk about all this stuff,

117
00:05:03,880 --> 00:05:06,559
Speaker 1: but it's not like now we're like, oh Newton, most

118
00:05:06,560 --> 00:05:08,880
Speaker 1: of what he said was wrong, But that's understandable because

119
00:05:08,920 --> 00:05:11,239
Speaker 1: it was a long time ago. Like his stuff holds

120
00:05:11,320 --> 00:05:12,680
Speaker 1: up really really well.

121
00:05:12,760 --> 00:05:15,520
Speaker 2: I was wondering if he on his deathbed was just like,

122
00:05:15,640 --> 00:05:20,440
Speaker 2: oh man, I contributed so much to humanity. It's mind boggling.

123
00:05:20,760 --> 00:05:22,479
Speaker 1: But I couldn't enhance my mailhood.

124
00:05:23,200 --> 00:05:26,800
Speaker 2: Well, Bob hadn't come along yet, so check. Let's just

125
00:05:26,960 --> 00:05:30,800
Speaker 2: quit stalling and talk about science, Like what is science?

126
00:05:31,160 --> 00:05:36,000
Speaker 1: Well, I hate the old elementary school defined as but

127
00:05:36,080 --> 00:05:38,320
Speaker 1: it's a pretty good place to start here to get

128
00:05:38,320 --> 00:05:39,960
Speaker 1: a base definition of science.

129
00:05:40,040 --> 00:05:42,080
Speaker 2: Yeah, Old William Harris did a great job with this.

130
00:05:42,360 --> 00:05:44,560
Speaker 1: Yes, William Harris did a great job. Yeah, he did

131
00:05:45,120 --> 00:05:48,680
Speaker 1: science the intellectual and practical activity encompassing the structure and

132
00:05:48,680 --> 00:05:52,560
Speaker 1: behavior of the physical and natural world through observation and experimentation.

133
00:05:53,040 --> 00:05:54,440
Speaker 2: Boom, end of podcast.

134
00:05:55,480 --> 00:05:58,600
Speaker 1: So the first part of that is science is practical

135
00:05:59,200 --> 00:06:02,240
Speaker 1: and it is you know, they make a good he makes.

136
00:06:02,480 --> 00:06:04,400
Speaker 1: Bill Harris makes a great point in here. It's not

137
00:06:04,600 --> 00:06:07,120
Speaker 1: just stuff you do in a lab, and it's not

138
00:06:07,279 --> 00:06:11,000
Speaker 1: just for scientists. It is all about being hands on

139
00:06:11,120 --> 00:06:14,400
Speaker 1: and active, and it's all about discovery and asking questions

140
00:06:14,800 --> 00:06:18,800
Speaker 1: about I mean, that's how everything is ultimately solved, is

141
00:06:18,839 --> 00:06:21,000
Speaker 1: by someone looking at something and having a question about

142
00:06:21,040 --> 00:06:21,680
Speaker 1: it exactly.

143
00:06:21,920 --> 00:06:24,280
Speaker 2: And then the scientific method comes in when you say,

144
00:06:24,360 --> 00:06:28,440
Speaker 2: and this is how you properly get to that answer exactly.

145
00:06:29,160 --> 00:06:32,520
Speaker 2: And he makes another good point too that the idea

146
00:06:32,560 --> 00:06:35,479
Speaker 2: that there is a method, a scientific method makes it

147
00:06:35,520 --> 00:06:42,000
Speaker 2: seem like it's it's secreted away, right, the fraternity of scientists,

148
00:06:42,040 --> 00:06:44,800
Speaker 2: And like you said, anybody can use it. It's this

149
00:06:44,920 --> 00:06:46,520
Speaker 2: kind of part of being a curious human.

150
00:06:46,839 --> 00:06:49,360
Speaker 1: It's not even anyone can use it. Everyone does use

151
00:06:49,400 --> 00:06:51,440
Speaker 1: it nice, you just might not even know that you're

152
00:06:51,560 --> 00:06:53,880
Speaker 1: using it, like if you I mean, one of the

153
00:06:53,880 --> 00:06:56,320
Speaker 1: examples that use later is if like your car overheats,

154
00:06:56,839 --> 00:06:59,839
Speaker 1: when you figure it out why and fix it, that's

155
00:06:59,839 --> 00:07:02,080
Speaker 1: the scientific method, right, playing.

156
00:07:01,800 --> 00:07:04,159
Speaker 2: Out exactly based on reasoning.

157
00:07:04,600 --> 00:07:07,000
Speaker 1: Yeah, okay, in deduction and induction.

158
00:07:07,360 --> 00:07:09,880
Speaker 2: Right man, there's so much to talk about, Okay, So

159
00:07:09,960 --> 00:07:13,160
Speaker 2: let's let's talk about that definition that you had. So

160
00:07:13,920 --> 00:07:16,280
Speaker 2: the first part is is that science is it's a

161
00:07:16,360 --> 00:07:20,360
Speaker 2: practical activity. So science is practical, right, Yeah, it's it's this.

162
00:07:22,320 --> 00:07:25,720
Speaker 2: The basis of the whole thing is discovery. Right. You

163
00:07:25,760 --> 00:07:28,600
Speaker 2: see something, you see birds in flight, and you say,

164
00:07:28,840 --> 00:07:32,120
Speaker 2: where are those birds going? And if you just went

165
00:07:32,160 --> 00:07:34,160
Speaker 2: and laid down on the ground and went to sleep

166
00:07:34,240 --> 00:07:37,200
Speaker 2: after that, then you're not you're not carrying out science.

167
00:07:37,240 --> 00:07:39,040
Speaker 2: But if you went, I want to find out where

168
00:07:39,040 --> 00:07:41,480
Speaker 2: those birds are going, and you follow them and you

169
00:07:41,520 --> 00:07:44,800
Speaker 2: start taking notes. That's that is the basis of science.

170
00:07:44,800 --> 00:07:45,560
Speaker 2: It's discovery.

171
00:07:45,680 --> 00:07:49,880
Speaker 1: Yeah, and that's the observational part as well. Sometimes you're

172
00:07:50,000 --> 00:07:53,200
Speaker 1: using a microscope or a telescope. Sometimes you're using your eyeballs.

173
00:07:53,720 --> 00:07:56,880
Speaker 1: But no matter what your tool is, you're going to

174
00:07:56,960 --> 00:08:01,720
Speaker 1: be watching something and recording what's called data or data,

175
00:08:01,760 --> 00:08:04,800
Speaker 1: depending on I don't know what kind of person you are.

176
00:08:05,160 --> 00:08:06,480
Speaker 2: Yeah, what do you say?

177
00:08:07,440 --> 00:08:08,280
Speaker 1: I think? I say both.

178
00:08:09,120 --> 00:08:11,680
Speaker 2: I think I say data, data. Yeah, I don't think.

179
00:08:11,680 --> 00:08:14,800
Speaker 2: I don't think. I say data, Okay, data, I say

180
00:08:14,880 --> 00:08:15,520
Speaker 2: data data.

181
00:08:15,640 --> 00:08:17,320
Speaker 1: Yeah, all right, we'll go with data.

182
00:08:17,400 --> 00:08:18,080
Speaker 2: You say both.

183
00:08:18,640 --> 00:08:20,120
Speaker 1: I feel like it just comes out of my mouth

184
00:08:20,160 --> 00:08:21,560
Speaker 1: one way or the other, and I don't really think

185
00:08:21,560 --> 00:08:21,920
Speaker 1: about it.

186
00:08:22,000 --> 00:08:24,119
Speaker 2: I think that's like being ambidextrous. Yeah.

187
00:08:24,240 --> 00:08:28,680
Speaker 1: Yeah, I'm a data data Yeah. Uh So once you

188
00:08:28,880 --> 00:08:31,880
Speaker 1: are observing this data, well, there are a couple of kinds.

189
00:08:32,080 --> 00:08:36,679
Speaker 1: There's quantitative data, which are numbers, like you know, your

190
00:08:36,720 --> 00:08:39,679
Speaker 1: body temperature is ninety eight point six. Although I think

191
00:08:39,679 --> 00:08:41,040
Speaker 1: that's changed slightly now, hadn't it.

192
00:08:41,360 --> 00:08:44,120
Speaker 2: Yeah? Yeah, there used to be like, if you were

193
00:08:44,160 --> 00:08:47,040
Speaker 2: a human being, your body temperature is ninety eight point six,

194
00:08:47,080 --> 00:08:49,080
Speaker 2: and then REALI like, no, it's a little more variation

195
00:08:49,240 --> 00:08:49,480
Speaker 2: than that.

196
00:08:49,600 --> 00:08:54,280
Speaker 1: Yeah, but any kind of just numerical representation is quantitative,

197
00:08:54,800 --> 00:08:59,040
Speaker 1: whereas qualitative is behavioral, like I'm going to watch that

198
00:08:59,120 --> 00:09:03,080
Speaker 1: bird eat and poop for the next week.

199
00:09:03,880 --> 00:09:06,600
Speaker 2: Right, Or what happens if I What will the slug

200
00:09:06,679 --> 00:09:08,400
Speaker 2: do if I put a bunch of salt on it?

201
00:09:09,280 --> 00:09:11,480
Speaker 2: You know, don't do that? No, you really should not

202
00:09:11,559 --> 00:09:11,840
Speaker 2: do that.

203
00:09:11,960 --> 00:09:12,760
Speaker 1: No, that's awful.

204
00:09:12,840 --> 00:09:16,679
Speaker 2: But the reaction of the slug is gathering qualitative data.

205
00:09:16,720 --> 00:09:20,239
Speaker 2: And depending on who you talk to, there isn't qualitative

206
00:09:20,320 --> 00:09:22,960
Speaker 2: data and science that it should all just be quantitative

207
00:09:23,040 --> 00:09:30,720
Speaker 2: because yeah, because quantitative data is reproducible. Qualitative data is

208
00:09:31,880 --> 00:09:35,679
Speaker 2: it's not necessarily reproducible. You can observe the same phenomenon,

209
00:09:35,920 --> 00:09:38,280
Speaker 2: but you're not necessarily controlling it.

210
00:09:38,960 --> 00:09:41,000
Speaker 1: Okay, well, I guess I get that. But I agree

211
00:09:41,040 --> 00:09:43,160
Speaker 1: with Bill here and that they are both they go

212
00:09:43,280 --> 00:09:45,800
Speaker 1: hand in hand. Yeah, and neither one is more important

213
00:09:45,800 --> 00:09:46,800
Speaker 1: than the other. You need to have both.

214
00:09:46,880 --> 00:09:48,640
Speaker 2: Well, a lot of people do, and we'll talk more

215
00:09:48,640 --> 00:09:51,920
Speaker 2: about it later, because without the idea that qualitative data

216
00:09:52,320 --> 00:09:56,839
Speaker 2: is acceptable and scientific, you don't have the social sciences,

217
00:09:56,840 --> 00:09:57,720
Speaker 2: Like they don't exist.

218
00:09:57,920 --> 00:09:59,000
Speaker 1: Yeah, that's a good point.

219
00:09:58,840 --> 00:10:03,319
Speaker 2: You know, But yes, we have quantitative data and qualitative data.

220
00:10:03,360 --> 00:10:05,360
Speaker 2: I agree with you, they're both useful.

221
00:10:05,520 --> 00:10:10,680
Speaker 1: Okay, it is an intellectual pursuit. So you can make

222
00:10:10,720 --> 00:10:14,680
Speaker 1: observations on data all day long. But until you bring reason,

223
00:10:14,760 --> 00:10:18,839
Speaker 1: in this case, inductive reasoning, which is driving a generalization

224
00:10:18,960 --> 00:10:23,720
Speaker 1: based on your observations, then it's just data sitting there

225
00:10:23,760 --> 00:10:25,720
Speaker 1: on a piece of paper like it's supposed to lead

226
00:10:25,800 --> 00:10:27,000
Speaker 1: you somewhere.

227
00:10:26,840 --> 00:10:29,640
Speaker 2: Right exactly, And so we should talk about inductive and

228
00:10:29,679 --> 00:10:33,079
Speaker 2: deductive reasoning and it depending. Again. It's really weird. One

229
00:10:33,080 --> 00:10:35,000
Speaker 2: of the things I came across is that there's not

230
00:10:35,880 --> 00:10:40,560
Speaker 2: a universal agreement on how science is carried out. Like

231
00:10:41,440 --> 00:10:43,280
Speaker 2: I've saw some places where there was like there's no

232
00:10:43,360 --> 00:10:47,920
Speaker 2: place for inductive reasoning in science. Then other places are saying, well,

233
00:10:47,960 --> 00:10:51,640
Speaker 2: you have to have science using inductive reasoning. Everybody seems

234
00:10:51,679 --> 00:10:56,120
Speaker 2: to agree that deductive reasoning is the basis of science, right,

235
00:10:56,160 --> 00:10:58,760
Speaker 2: but that you also have to have inductive So deductive

236
00:10:58,800 --> 00:11:04,120
Speaker 2: is basically taking a big broad generalization and saying that

237
00:11:04,320 --> 00:11:05,680
Speaker 2: it applies to.

238
00:11:05,600 --> 00:11:07,760
Speaker 1: Something specific more specific.

239
00:11:07,920 --> 00:11:12,800
Speaker 2: Yes, inductive is the opposite where you say, I've noticed

240
00:11:12,840 --> 00:11:19,200
Speaker 2: these different data points, and that means that this broad

241
00:11:19,280 --> 00:11:23,719
Speaker 2: generalization is true. So you go from specific, small observations

242
00:11:23,760 --> 00:11:26,560
Speaker 2: to a broad generalization. And the reason that a lot

243
00:11:26,600 --> 00:11:29,679
Speaker 2: of people say, well, inductive reasoning doesn't have any place

244
00:11:29,720 --> 00:11:35,160
Speaker 2: in science is because you're saying, those birds over there

245
00:11:35,600 --> 00:11:39,199
Speaker 2: are all brown. Therefore all birds of that type are brown.

246
00:11:39,360 --> 00:11:41,440
Speaker 2: Even though I haven't seen every single bird of that

247
00:11:41,480 --> 00:11:44,240
Speaker 2: type in the world. I'm saying that all those birds

248
00:11:44,520 --> 00:11:46,560
Speaker 2: are brown, And a lot of people say there's no

249
00:11:46,559 --> 00:11:47,600
Speaker 2: place for that in science.

250
00:11:48,120 --> 00:11:49,960
Speaker 1: Well, if you want to go out and prove that,

251
00:11:50,000 --> 00:11:52,880
Speaker 1: then that's your business. You know. You can't just say

252
00:11:52,880 --> 00:11:55,720
Speaker 1: that and be like, and I'm done, right exactly, I

253
00:11:55,720 --> 00:11:58,559
Speaker 1: guess you could but be much of a scientist, right, but.

254
00:12:00,280 --> 00:12:03,200
Speaker 2: Use it to formulate, hey hypotheses. Sure, right, So you

255
00:12:03,200 --> 00:12:06,080
Speaker 2: can say I've generated all these data points, I'm gonna

256
00:12:06,080 --> 00:12:10,800
Speaker 2: put them together and see if this broad generalization is right. Okay,

257
00:12:10,880 --> 00:12:12,920
Speaker 2: so there is a place for inductive reasoning science. But

258
00:12:12,960 --> 00:12:16,760
Speaker 2: everybody says deductive reasoning is the basis of science.

259
00:12:17,240 --> 00:12:21,840
Speaker 1: Well, Bill Harris does. He offers a great example for

260
00:12:22,120 --> 00:12:27,120
Speaker 1: inductive reasoning with Edwin Hubble of the Hubble Telescope. He

261
00:12:27,320 --> 00:12:30,800
Speaker 1: was looking through the Hooker telescope which at the time

262
00:12:31,000 --> 00:12:33,360
Speaker 1: at California's Mount Wilson.

263
00:12:33,520 --> 00:12:35,400
Speaker 2: Is that the one from Rebel Without a Cause?

264
00:12:35,720 --> 00:12:41,800
Speaker 1: No, that's Griffith Park Observatory, which has been redesigned and

265
00:12:42,920 --> 00:12:44,719
Speaker 1: is really cool now, is it. Yeah. I mean it

266
00:12:44,760 --> 00:12:46,560
Speaker 1: was kind of cool before, but it was definitely like

267
00:12:47,120 --> 00:12:51,480
Speaker 1: sort of the base museum that time forgot. Oh really,

268
00:12:51,520 --> 00:12:52,360
Speaker 1: so they've updated it.

269
00:12:52,400 --> 00:12:54,240
Speaker 2: I'll bet that was cool though in its own way.

270
00:12:54,400 --> 00:12:55,839
Speaker 1: Yeah, it was neat. I used to live near there,

271
00:12:55,920 --> 00:12:56,760
Speaker 1: so it was kind of.

272
00:12:56,800 --> 00:12:59,280
Speaker 2: But that's like the famous one, at least in the movies.

273
00:12:59,480 --> 00:13:01,480
Speaker 1: Yeah, that's where they have the big knife fight. Yeah,

274
00:13:01,520 --> 00:13:03,520
Speaker 1: and there's this James Deane statue there too.

275
00:13:03,679 --> 00:13:06,719
Speaker 2: Oh I didn't like a bust.

276
00:13:07,040 --> 00:13:10,360
Speaker 1: So yes. Edwin Hubble he's at mountin Wilson and he's

277
00:13:10,360 --> 00:13:12,920
Speaker 1: looking through the Hooker telescope, which was the biggest one

278
00:13:13,000 --> 00:13:15,960
Speaker 1: and at the time everyone said the Milky Way Galaxy

279
00:13:16,040 --> 00:13:17,920
Speaker 1: is it? That's what we've got going on?

280
00:13:18,240 --> 00:13:18,800
Speaker 2: Did you know this?

281
00:13:19,800 --> 00:13:20,040
Speaker 1: Yeah?

282
00:13:20,040 --> 00:13:22,400
Speaker 2: I knew that because we're talking nineteen nineteen.

283
00:13:22,600 --> 00:13:25,080
Speaker 1: Yeah, not that long ago. He did not realize this,

284
00:13:25,160 --> 00:13:27,520
Speaker 1: and he started looking through the telescope and said, you

285
00:13:27,600 --> 00:13:30,160
Speaker 1: know what these nebula that everyone says they're part of

286
00:13:30,200 --> 00:13:33,880
Speaker 1: our galaxy, looked to me like they're beyond our galaxy.

287
00:13:34,160 --> 00:13:36,400
Speaker 1: And not only that, they look like they're moving away

288
00:13:36,440 --> 00:13:40,839
Speaker 1: from us. So he made this with through inductive reasoning,

289
00:13:40,920 --> 00:13:43,560
Speaker 1: made this observation that you know what, I think there

290
00:13:43,640 --> 00:13:47,000
Speaker 1: are many many galaxies out there, and not only that,

291
00:13:47,080 --> 00:13:51,760
Speaker 1: I think they are expanding. Yeah, and through technological advancement

292
00:13:51,800 --> 00:13:55,040
Speaker 1: with telescopes over the years, scientists, you know, it proved

293
00:13:55,160 --> 00:13:55,760
Speaker 1: to be true.

294
00:13:56,200 --> 00:13:58,760
Speaker 2: Yeah. Pretty cool. So this is a really good example

295
00:13:58,800 --> 00:14:02,319
Speaker 2: of him saying, like, I've made some observations and now

296
00:14:02,360 --> 00:14:06,520
Speaker 2: I'm going to say this broad generalization. Right, So these

297
00:14:07,200 --> 00:14:10,520
Speaker 2: these galaxies appear to be moving away from me another,

298
00:14:10,600 --> 00:14:15,360
Speaker 2: so the whole universe is expanding. Right, that's inductive reasoning.

299
00:14:15,440 --> 00:14:19,120
Speaker 1: Yeah, it's a pretty brave thing, especially back then, because

300
00:14:19,120 --> 00:14:21,480
Speaker 1: you're really putting your reputation at stake.

301
00:14:21,640 --> 00:14:24,400
Speaker 2: It really is, you know. So what Hubble was, what

302
00:14:24,520 --> 00:14:28,000
Speaker 2: Hubble did was what we've come to see as science.

303
00:14:28,040 --> 00:14:31,680
Speaker 2: He made some observations, he came up with a hypothesis,

304
00:14:32,800 --> 00:14:35,680
Speaker 2: and then it was tested later on. It's not you

305
00:14:35,720 --> 00:14:39,320
Speaker 2: don't necessarily as a scientist. You're a part of a

306
00:14:39,400 --> 00:14:44,240
Speaker 2: larger collective of scientists yes, right, And every scientist needs

307
00:14:44,240 --> 00:14:48,600
Speaker 2: one another. It's why there's journals and conferences and things

308
00:14:48,640 --> 00:14:50,240
Speaker 2: like that to share information.

309
00:14:49,920 --> 00:14:51,800
Speaker 1: Right into party, right, and to party.

310
00:14:52,160 --> 00:14:55,400
Speaker 2: And Hubble came up with his own observations, and rather

311
00:14:55,480 --> 00:14:59,440
Speaker 2: than just experimenting and experimenting, experimenting himself, which I'm sure

312
00:14:59,440 --> 00:15:02,800
Speaker 2: he continued to do, he created this basis of work

313
00:15:02,880 --> 00:15:07,120
Speaker 2: that he probably realized is going to survive him. Yeah, yeah, right.

314
00:15:07,520 --> 00:15:10,320
Speaker 2: And then later on scientists came down the road and

315
00:15:10,400 --> 00:15:14,760
Speaker 2: they tested his hypothesis and they found it was correct,

316
00:15:15,160 --> 00:15:18,040
Speaker 2: and so his hypothesis became a theory. It eventually became

317
00:15:18,120 --> 00:15:20,360
Speaker 2: part of the basis of the Big Bang theory that

318
00:15:20,400 --> 00:15:24,760
Speaker 2: the universe started as a huge explosion and it's expanding

319
00:15:24,920 --> 00:15:28,880
Speaker 2: still because we're because it exploded at one point, right.

320
00:15:29,560 --> 00:15:32,120
Speaker 2: And they did that by carrying out other.

321
00:15:32,480 --> 00:15:35,400
Speaker 1: Tests or experiments exactly.

322
00:15:35,960 --> 00:15:38,280
Speaker 2: So this is how science works. Like some guy back

323
00:15:38,320 --> 00:15:42,080
Speaker 2: in nineteen ninety makes some observations in California in nineteen

324
00:15:42,160 --> 00:15:47,120
Speaker 2: twenty five, he proposes this big broad generalization, and over

325
00:15:47,120 --> 00:15:50,680
Speaker 2: the next like ensuing half a century, more and more

326
00:15:50,720 --> 00:15:54,960
Speaker 2: scientists all around the world start testing his hypothesis and

327
00:15:55,080 --> 00:15:57,000
Speaker 2: find it to be true. So it becomes a theory.

328
00:15:57,240 --> 00:16:00,480
Speaker 1: Yeah. Well, well let's finish up here with sience Oka.

329
00:16:00,760 --> 00:16:04,240
Speaker 1: The last part of the definition is that it's systematic,

330
00:16:04,320 --> 00:16:09,120
Speaker 1: and it's methodical, and it requires testing and experiments, and

331
00:16:09,200 --> 00:16:15,080
Speaker 1: that requires those experiments and tests to be repeated and verified.

332
00:16:15,760 --> 00:16:20,120
Speaker 1: And it's a system. It's a way of working things out.

333
00:16:20,280 --> 00:16:22,640
Speaker 1: It's a way of working Yeah. That is the scientific

334
00:16:22,680 --> 00:16:26,600
Speaker 1: method basically. Yeah, you have your idea, you pose a question,

335
00:16:27,360 --> 00:16:31,040
Speaker 1: you theorize, or you put a hypothesis out there, and

336
00:16:31,080 --> 00:16:33,160
Speaker 1: then you go about trying to either prove it or

337
00:16:33,160 --> 00:16:33,680
Speaker 1: disprove it.

338
00:16:34,000 --> 00:16:36,040
Speaker 2: Yeah, exactly. And then the way that you go about

339
00:16:36,160 --> 00:16:39,800
Speaker 2: proving or disproving it, that's the scientific method. Everything else

340
00:16:39,880 --> 00:16:43,440
Speaker 2: is just scientific inquiry. The way you go about, the

341
00:16:43,520 --> 00:16:47,360
Speaker 2: standardized way of going about scientific inquiry is the scientific method.

342
00:16:47,640 --> 00:16:51,120
Speaker 2: And we, friend, we'll talk about the scientific method right

343
00:16:51,160 --> 00:16:51,520
Speaker 2: after this.

344
00:17:08,119 --> 00:17:10,199
Speaker 1: All right, you brought up a point. I think we

345
00:17:10,200 --> 00:17:12,680
Speaker 1: should go ahead and just get right to my friend,

346
00:17:12,760 --> 00:17:15,159
Speaker 1: let's do it. Hypotheses and theories.

347
00:17:16,160 --> 00:17:18,040
Speaker 2: One thing tough to say together. I know.

348
00:17:18,960 --> 00:17:24,000
Speaker 1: One thing that really chafes my hide is when you

349
00:17:24,040 --> 00:17:27,680
Speaker 1: hear poopoo ers of whatever scientific theory say, well, it's

350
00:17:27,720 --> 00:17:30,280
Speaker 1: just a theory. Yeah, and you where was this thing

351
00:17:30,320 --> 00:17:34,000
Speaker 1: that you found that poopoo that Do you remember what

352
00:17:34,119 --> 00:17:34,919
Speaker 1: website that was?

353
00:17:36,880 --> 00:17:39,440
Speaker 2: No, No, although I do want to give a shout

354
00:17:39,440 --> 00:17:42,240
Speaker 2: out now that you mentioned it. Two explorables. Yeah, it's

355
00:17:42,240 --> 00:17:47,240
Speaker 2: like an online university, basically a free courses and there

356
00:17:47,400 --> 00:17:50,960
Speaker 2: is one on scientific reasoning that is just amazing. It's

357
00:17:51,040 --> 00:17:53,000
Speaker 2: like a huge rabbit hole. You go down and you

358
00:17:53,200 --> 00:17:56,040
Speaker 2: start clicking on the embedded links and you end up

359
00:17:56,080 --> 00:17:59,280
Speaker 2: like understanding all sorts of stuff. So go check that.

360
00:17:59,240 --> 00:18:02,880
Speaker 1: One out if you like understanding stuff. Right, So that's

361
00:18:02,880 --> 00:18:04,440
Speaker 1: one of the things that bugged me if someone says

362
00:18:04,440 --> 00:18:06,720
Speaker 1: it's just a theory, and this does a great job

363
00:18:06,760 --> 00:18:10,800
Speaker 1: of kind of throwing that out the window because it's

364
00:18:10,800 --> 00:18:13,800
Speaker 1: basically mixing up the two definitions of theory.

365
00:18:14,000 --> 00:18:17,120
Speaker 2: Yeah, there's like a colloquial definition that people use every

366
00:18:17,160 --> 00:18:19,480
Speaker 2: day that doesn't really have much to do with the

367
00:18:19,520 --> 00:18:20,520
Speaker 2: scientific cuses.

368
00:18:20,359 --> 00:18:23,960
Speaker 1: Like, I got a theory that Jerry and one hour

369
00:18:24,000 --> 00:18:28,520
Speaker 1: bathroom breaks every day is really playing words with friends

370
00:18:29,440 --> 00:18:30,120
Speaker 1: in the lobby.

371
00:18:30,640 --> 00:18:32,040
Speaker 2: I think your theory is correct.

372
00:18:32,240 --> 00:18:36,879
Speaker 1: So that's a theory in the colloquial meaning as far

373
00:18:36,880 --> 00:18:41,760
Speaker 1: as science goes. A theory is not just something you postulate, say,

374
00:18:41,880 --> 00:18:44,040
Speaker 1: this may or may not be true. A theory is

375
00:18:44,119 --> 00:18:48,080
Speaker 1: beyond the hypothesis, and it's something that is strongly supported

376
00:18:48,600 --> 00:18:52,080
Speaker 1: in many different ways and all there's all kinds of

377
00:18:52,080 --> 00:18:55,000
Speaker 1: evidence to support something that eventually becomes a theory.

378
00:18:55,119 --> 00:18:59,359
Speaker 2: Right, So what you your theory about Jerry's bathroom breaks

379
00:18:59,800 --> 00:19:05,240
Speaker 2: this scientific world would be a hypothesis. What fact, it

380
00:19:05,320 --> 00:19:08,920
Speaker 2: would be a scientific law, but it ultimately would begin

381
00:19:09,000 --> 00:19:13,199
Speaker 2: as a hypothesis, a hunch based on intuition, based on

382
00:19:13,880 --> 00:19:17,600
Speaker 2: data you've collected, observations, that kind of stuff. Where Like,

383
00:19:17,680 --> 00:19:20,920
Speaker 2: you know, you've seen that Jerry goes to the bathroom

384
00:19:21,000 --> 00:19:24,600
Speaker 2: for like an hour to stretch frequently. When she comes back,

385
00:19:24,680 --> 00:19:28,760
Speaker 2: she's finishing up a game of words with friends. Sure,

386
00:19:29,359 --> 00:19:32,240
Speaker 2: you've heard that she's been spotted in the lobby during

387
00:19:32,280 --> 00:19:36,560
Speaker 2: these times. So your hypothesis is that while she is

388
00:19:36,640 --> 00:19:39,240
Speaker 2: gone for these hour long bathroom breaks, she's actually down

389
00:19:39,280 --> 00:19:40,560
Speaker 2: the lobby playing words with friends.

390
00:19:40,600 --> 00:19:44,280
Speaker 1: Right, Yeah, based on knowledge, observation, and logic. Right.

391
00:19:44,320 --> 00:19:46,920
Speaker 2: So let's say that you decided to set up an experiment,

392
00:19:47,000 --> 00:19:49,639
Speaker 2: and you experimented, and you went and you found Jerry

393
00:19:49,640 --> 00:19:53,199
Speaker 2: playing words with friends. Yeah, five different times, and you

394
00:19:53,359 --> 00:19:55,720
Speaker 2: told me about it, and I was like, I'm going

395
00:19:55,760 --> 00:19:59,080
Speaker 2: to run that same experiment exactly the way you did. Yeah, right,

396
00:19:59,560 --> 00:20:02,520
Speaker 2: I would test that same hypothsis. If I found the

397
00:20:02,520 --> 00:20:05,119
Speaker 2: same results to be true, then what you would have

398
00:20:05,200 --> 00:20:08,199
Speaker 2: come up with, your hypothesis would move to basically a

399
00:20:08,320 --> 00:20:12,840
Speaker 2: theory that is, this widely accepted thing, this explanation that

400
00:20:13,440 --> 00:20:17,520
Speaker 2: Jerry is not actually in the bathroom, she's downstairs playing

401
00:20:17,520 --> 00:20:21,440
Speaker 2: with friends. It'd be the Jerry bathroom break theory, that's right.

402
00:20:21,760 --> 00:20:25,400
Speaker 2: And then if it turns out that you find that

403
00:20:25,800 --> 00:20:29,040
Speaker 2: Jerry spending an hour a day pretending to be in

404
00:20:29,080 --> 00:20:33,680
Speaker 2: the bathroom but actually being downstairs playing words with friends,

405
00:20:35,320 --> 00:20:39,240
Speaker 2: if the universe couldn't exist without her doing that every day, yeah,

406
00:20:39,480 --> 00:20:41,880
Speaker 2: you would have a scientific law.

407
00:20:41,800 --> 00:20:42,240
Speaker 1: That's right.

408
00:20:43,320 --> 00:20:45,879
Speaker 2: Yeah, I think that was a good example you came

409
00:20:45,960 --> 00:20:46,159
Speaker 2: up with.

410
00:20:46,200 --> 00:20:49,960
Speaker 1: Well, that's a great example, as it turns out. I

411
00:20:50,000 --> 00:20:52,399
Speaker 1: guess the point here is when you hear someone say

412
00:20:52,880 --> 00:20:56,040
Speaker 1: in an argument, well that's just a theory, just punch

413
00:20:56,119 --> 00:20:58,119
Speaker 1: him in the head and then tell them what we

414
00:20:58,280 --> 00:20:59,960
Speaker 1: just said about the bathroom breaks.

415
00:21:00,080 --> 00:21:03,440
Speaker 2: Yeah, and they'll say, who's cherry or just queue up

416
00:21:03,600 --> 00:21:07,520
Speaker 2: that whole bit and stand outside of their window wearing

417
00:21:07,520 --> 00:21:09,439
Speaker 2: a trench coat and holding a boom box over your

418
00:21:09,480 --> 00:21:11,720
Speaker 2: head with the smug look on your face.

419
00:21:13,600 --> 00:21:15,880
Speaker 1: All right, So should we go back in the old

420
00:21:15,880 --> 00:21:17,720
Speaker 1: way back machine a little bit and just talk a

421
00:21:17,720 --> 00:21:20,000
Speaker 1: little bit about how the scientific method came to be?

422
00:21:20,520 --> 00:21:32,000
Speaker 2: Yes, man, this this thing? What are you running this

423
00:21:32,119 --> 00:21:36,480
Speaker 2: on these days? A straight kerosene? The fumes in here

424
00:21:36,520 --> 00:21:37,199
Speaker 2: are killing me.

425
00:21:37,640 --> 00:21:39,600
Speaker 1: Sorry about that. I'm trying to go green.

426
00:21:39,760 --> 00:21:41,720
Speaker 2: You know, kerosene is not green.

427
00:21:43,000 --> 00:21:47,639
Speaker 1: Diesel. Maybe I'm choking biodiesel? How about that? Okay, the

428
00:21:47,640 --> 00:21:50,040
Speaker 1: way back machine will run French fried grease. That would

429
00:21:50,080 --> 00:21:52,320
Speaker 1: be fine, right, I'll get to work on that. I

430
00:21:52,359 --> 00:21:56,040
Speaker 1: could handle this few So you tease this with the Renaissance,

431
00:21:56,080 --> 00:21:59,200
Speaker 1: and the reason the Renaissance was so awesome and necessary

432
00:21:59,240 --> 00:22:01,920
Speaker 1: it was because of something else we've talked about, which

433
00:22:02,000 --> 00:22:03,360
Speaker 1: was the Dark Ages.

434
00:22:04,359 --> 00:22:10,120
Speaker 2: Which remember that's a rationalist's disparaging term for this era.

435
00:22:10,280 --> 00:22:14,920
Speaker 1: That's right, but I think sort of rightfully so, because

436
00:22:15,400 --> 00:22:17,840
Speaker 1: right before the Dark Ages until about a century after,

437
00:22:18,280 --> 00:22:21,520
Speaker 1: there was not much advancement at all in the realm

438
00:22:21,560 --> 00:22:22,800
Speaker 1: of scientific advancement.

439
00:22:24,440 --> 00:22:26,919
Speaker 2: No, it's true, it's hard to argue with that, and

440
00:22:26,960 --> 00:22:30,280
Speaker 2: The reason why is again, science wasn't really born yet,

441
00:22:30,640 --> 00:22:34,320
Speaker 2: and there is a huge struggle between rationalism and mysticism,

442
00:22:34,400 --> 00:22:38,000
Speaker 2: and ultimately we're living in the age of rationalism now.

443
00:22:38,240 --> 00:22:40,240
Speaker 1: Yeah, and we should point out too that this was

444
00:22:40,359 --> 00:22:44,080
Speaker 1: mainly in Europe over in the Islamic world. As I

445
00:22:44,119 --> 00:22:46,159
Speaker 1: think we had a listener mail point out, there were

446
00:22:46,160 --> 00:22:49,320
Speaker 1: a lot of advancements being made just sort of flying

447
00:22:49,440 --> 00:22:53,720
Speaker 1: under the European radar at the time, because some say

448
00:22:53,800 --> 00:22:56,800
Speaker 1: the Catholic Church kind of kept science under its thumb

449
00:22:56,880 --> 00:22:59,639
Speaker 1: for a while. Yeah, and it's a pretty big threat

450
00:23:00,880 --> 00:23:02,480
Speaker 1: and said, you know, you can't do this stuff, you

451
00:23:02,520 --> 00:23:05,600
Speaker 1: can't experiment like this, and don't ask these questions, right

452
00:23:06,280 --> 00:23:09,920
Speaker 1: because here are your answers. Yeah. But eventually the Renaissance

453
00:23:10,000 --> 00:23:12,720
Speaker 1: came about in the twelfth century and people woke up

454
00:23:12,760 --> 00:23:15,640
Speaker 1: and saw some of the work in the Islamic world

455
00:23:15,680 --> 00:23:18,040
Speaker 1: and said, you know what, maybe let's start reading up

456
00:23:18,040 --> 00:23:20,920
Speaker 1: on Aristotle and tootle of me and euclid it once again.

457
00:23:21,040 --> 00:23:23,359
Speaker 2: Yeah, they're like, we forgot about these guys.

458
00:23:23,560 --> 00:23:26,000
Speaker 1: Yeah, I mean it literally kind of vanished for a while, it.

459
00:23:26,000 --> 00:23:29,520
Speaker 2: Did from the West. Yes, Fortunately it was still around,

460
00:23:29,640 --> 00:23:32,520
Speaker 2: you know, in its home places. But yes, in the

461
00:23:32,560 --> 00:23:35,720
Speaker 2: West they were lost. The Roman stuff was almost entirely

462
00:23:35,800 --> 00:23:38,560
Speaker 2: lost because it was being suppressed by the locals.

463
00:23:38,720 --> 00:23:41,520
Speaker 1: And I think the Greek knowledge was completely vanished.

464
00:23:41,760 --> 00:23:45,360
Speaker 2: Yes, somehow, somehow they got there was some We got

465
00:23:45,400 --> 00:23:47,879
Speaker 2: another listener mail after the Enlightenment. One they said that

466
00:23:47,960 --> 00:23:51,879
Speaker 2: it was an Islamic scholar who was the one who

467
00:23:52,240 --> 00:23:57,680
Speaker 2: translated Aristotle right into Latin or something like that, and

468
00:23:57,720 --> 00:24:00,560
Speaker 2: that without this guy, like the West wouldn't have had

469
00:24:00,680 --> 00:24:03,600
Speaker 2: much to start with. Because that's where that birth of

470
00:24:03,720 --> 00:24:07,919
Speaker 2: rationalism came from, was this rediscovery of Greek and Roman

471
00:24:08,040 --> 00:24:12,520
Speaker 2: classical thought. And this was the basis of scientific inquiry,

472
00:24:12,560 --> 00:24:16,359
Speaker 2: of rationalism, of saying, like, okay, there's set rules to things,

473
00:24:16,359 --> 00:24:18,520
Speaker 2: and we need to discover these rules and how the

474
00:24:19,080 --> 00:24:21,600
Speaker 2: principles of how the universe works, like there has to

475
00:24:21,640 --> 00:24:23,960
Speaker 2: be principles, and we need to find this in a rational,

476
00:24:24,000 --> 00:24:29,000
Speaker 2: methodical way. And right out of the gate, Europe said, oh, okay,

477
00:24:29,040 --> 00:24:31,919
Speaker 2: well whatever you say is right, then, Aristotle, We're used

478
00:24:31,960 --> 00:24:35,119
Speaker 2: to just believing everything without questioning it. Yeah, And luckily

479
00:24:35,240 --> 00:24:37,080
Speaker 2: albert Magnus, I think is who it was.

480
00:24:37,840 --> 00:24:38,520
Speaker 1: Albertus.

481
00:24:38,800 --> 00:24:41,600
Speaker 2: Was it Albertus Magnus or Roger Bacon, who said, no,

482
00:24:41,680 --> 00:24:44,840
Speaker 2: it is Bacon. Roger Bacon, who just has this great name,

483
00:24:45,119 --> 00:24:46,720
Speaker 2: Roger Bacon.

484
00:24:46,480 --> 00:24:50,800
Speaker 1: The Bacon brothers. Yeah, he says, Roger, Right, they weren't brothers,

485
00:24:51,040 --> 00:24:53,000
Speaker 1: But were they related at all? You know, I look

486
00:24:53,080 --> 00:24:56,640
Speaker 1: that up and I don't think people know either way.

487
00:24:56,720 --> 00:24:58,480
Speaker 1: I don't think there's any proof, but a lot of

488
00:24:58,480 --> 00:25:01,200
Speaker 1: people think because of the names and the way things

489
00:25:01,240 --> 00:25:04,240
Speaker 1: went back then, that they may very well have been lighted.

490
00:25:04,359 --> 00:25:06,560
Speaker 2: And I mean they were separated by three hundred or

491
00:25:06,600 --> 00:25:07,240
Speaker 2: so years.

492
00:25:07,520 --> 00:25:10,680
Speaker 1: Although Roger was a was a monk, so he would

493
00:25:10,680 --> 00:25:13,440
Speaker 1: not have had children. So if they were, it's an

494
00:25:13,440 --> 00:25:16,879
Speaker 1: excellent point. It wasn't necessarily through his line, gotcha, you know.

495
00:25:17,080 --> 00:25:19,639
Speaker 2: Yeah, it could have been a nephew or something.

496
00:25:19,760 --> 00:25:23,400
Speaker 1: Yeah, or his brother Kevin might have had the line

497
00:25:23,440 --> 00:25:23,960
Speaker 1: that matched.

498
00:25:24,280 --> 00:25:27,399
Speaker 2: So Roger was the one who said, everybody stopped. Just

499
00:25:27,440 --> 00:25:31,359
Speaker 2: because Aristotle wrote something doesn't mean it's fact, especially when

500
00:25:31,680 --> 00:25:35,760
Speaker 2: we find contradictions to it. Yeah, it doesn't Aircell's not

501
00:25:35,800 --> 00:25:37,960
Speaker 2: automatically right, and this is a huge advancement.

502
00:25:38,520 --> 00:25:42,200
Speaker 1: Yeah. And Albertus Magnus was the one, I believe who said,

503
00:25:43,560 --> 00:25:47,240
Speaker 1: you know this thing called revealed truth, which is basically

504
00:25:47,520 --> 00:25:51,440
Speaker 1: God says this instead of a truth found by experimenting,

505
00:25:52,080 --> 00:25:55,479
Speaker 1: is maybe we should experiment instead and not take this

506
00:25:55,560 --> 00:25:57,200
Speaker 1: revealed truth as the truth.

507
00:25:57,400 --> 00:26:00,240
Speaker 2: Right. And we mentioned in the Enlightenment episode of Well

508
00:26:00,240 --> 00:26:06,640
Speaker 2: about scholasticism, about using scientific inquiry to explain theology, right,

509
00:26:06,680 --> 00:26:10,720
Speaker 2: which was, you know, you're still working from a theological standpoint,

510
00:26:10,960 --> 00:26:15,320
Speaker 2: but you're starting to use scientific inquiry and the the

511
00:26:15,480 --> 00:26:18,359
Speaker 2: idea that you shouldn't just accept things as truth. That

512
00:26:18,520 --> 00:26:20,520
Speaker 2: was again a huge, huge breakthrough.

513
00:26:20,680 --> 00:26:24,040
Speaker 1: Yeah. Uh. Francis Bacon, the other Bacon.

514
00:26:23,920 --> 00:26:25,919
Speaker 2: Brother, he's one of the heroes of this story.

515
00:26:26,040 --> 00:26:30,480
Speaker 1: Yeah, he was an attorney and philosopher and possibly Shakespeare.

516
00:26:31,119 --> 00:26:31,840
Speaker 2: Oh really, huh?

517
00:26:31,920 --> 00:26:36,800
Speaker 1: I never heard that. Oh yeah, interesting. So what do

518
00:26:36,840 --> 00:26:40,400
Speaker 1: you mean, like wrote those under the a pseudonym? Yeah, huh.

519
00:26:40,640 --> 00:26:42,760
Speaker 1: And then the Shakespeare sister was the other theory too,

520
00:26:42,840 --> 00:26:45,400
Speaker 1: Right it was a woman. I've heard that, Yeah, and

521
00:26:45,440 --> 00:26:48,680
Speaker 1: she couldn't, like, you know, women couldn't be the playwright.

522
00:26:48,800 --> 00:26:50,840
Speaker 1: So that's her dumb brother, William.

523
00:26:50,920 --> 00:26:52,720
Speaker 2: That's a good credit, was it her brother?

524
00:26:53,480 --> 00:26:54,959
Speaker 1: I think that was one of the theories.

525
00:26:55,080 --> 00:26:57,359
Speaker 2: Huh. This was a good Smith song too.

526
00:26:58,560 --> 00:27:01,000
Speaker 1: Uh. Shakespeare sister? Is that the name of it. Yeah,

527
00:27:01,560 --> 00:27:02,440
Speaker 1: wasn't it a band too?

528
00:27:03,600 --> 00:27:04,960
Speaker 2: I think it was? What was it?

529
00:27:05,000 --> 00:27:10,199
Speaker 1: Maybe? So anyway, he was a philosopher and a lawyer,

530
00:27:10,800 --> 00:27:15,879
Speaker 1: and he said, you know what, the Baconian method basically

531
00:27:15,880 --> 00:27:17,320
Speaker 1: became the scientific method.

532
00:27:17,440 --> 00:27:17,720
Speaker 2: Yeah.

533
00:27:17,800 --> 00:27:20,480
Speaker 1: He was the first dude who really said, this is

534
00:27:20,880 --> 00:27:24,959
Speaker 1: how the steps that you should take to investigate science.

535
00:27:25,160 --> 00:27:27,280
Speaker 2: Right, there has to be a framework. And the whole

536
00:27:27,320 --> 00:27:30,480
Speaker 2: point of this that we take this so for granted

537
00:27:30,520 --> 00:27:37,359
Speaker 2: now because it's so intuitively and on its face, right, yeah,

538
00:27:37,440 --> 00:27:40,080
Speaker 2: as far as scienceific inquiry goes. But this is an

539
00:27:40,240 --> 00:27:44,560
Speaker 2: enormous breakthrough to say, you follow this step, these steps,

540
00:27:44,640 --> 00:27:49,760
Speaker 2: this framework, and if everybody who carries out science follows

541
00:27:49,760 --> 00:27:54,040
Speaker 2: the same framework, then science will be universal and interchangeable

542
00:27:54,400 --> 00:27:58,200
Speaker 2: and anyone in the world and not just now, but anytime. Yeah,

543
00:27:58,320 --> 00:28:02,280
Speaker 2: we'll be able to carry out the same experiment and

544
00:28:02,600 --> 00:28:05,719
Speaker 2: we'll be able to verify or disprove it. Yeah, and

545
00:28:06,000 --> 00:28:10,600
Speaker 2: that is amazing that that happened. That's why Francis Bacon

546
00:28:10,640 --> 00:28:12,040
Speaker 2: is one of the heroes of the story. And he

547
00:28:12,040 --> 00:28:14,520
Speaker 2: didn't come up with this entirely on his own, but

548
00:28:14,640 --> 00:28:17,120
Speaker 2: he was the one who said this is what we're

549
00:28:17,119 --> 00:28:18,800
Speaker 2: going to do. I'm going to give it a name.

550
00:28:19,040 --> 00:28:21,520
Speaker 2: I'm going to spell it out, and from now on

551
00:28:21,880 --> 00:28:25,359
Speaker 2: you can call me the dad of the scientific method.

552
00:28:25,640 --> 00:28:28,000
Speaker 1: Yeah. And that's why Newton was such a rock star,

553
00:28:28,080 --> 00:28:32,239
Speaker 1: because he's so rigorously stuck to the scientific method that

554
00:28:32,320 --> 00:28:35,920
Speaker 1: all these centuries later, his you know, his systems of

555
00:28:36,000 --> 00:28:38,200
Speaker 1: laws are they have stood the test of time.

556
00:28:38,360 --> 00:28:38,719
Speaker 2: Yeah.

557
00:28:38,760 --> 00:28:40,840
Speaker 1: And I think it's a good point to bring up

558
00:28:40,840 --> 00:28:47,120
Speaker 1: to that the collaboration of scientists is really the hallmark

559
00:28:47,280 --> 00:28:52,520
Speaker 1: of advancement and moving forward. It's not working in a vacuum.

560
00:28:52,720 --> 00:28:55,280
Speaker 1: It's sharing your ideas and working with one another. And

561
00:28:55,880 --> 00:28:58,840
Speaker 1: the whole little sidebar here on self theory I thought

562
00:28:58,920 --> 00:29:03,040
Speaker 1: was pretty cool, which was when science quit or not quit,

563
00:29:03,160 --> 00:29:06,680
Speaker 1: but started looking at small things instead of looking at

564
00:29:06,720 --> 00:29:11,480
Speaker 1: the universe around them and at the stars. Right, and said, basically,

565
00:29:11,920 --> 00:29:16,760
Speaker 1: you know, through the advancement of lens grinding, Antonio van Levin'

566
00:29:16,760 --> 00:29:20,960
Speaker 1: Hook specifically a Dutch tradesman, was pretty good at making

567
00:29:20,960 --> 00:29:24,480
Speaker 1: simple microscopes, and all of a sudden, contemporaries like Robert

568
00:29:24,520 --> 00:29:26,880
Speaker 1: Hook said, you know what, let's start looking at tiny

569
00:29:26,920 --> 00:29:30,680
Speaker 1: things because therein might lie the answer to many many things.

570
00:29:30,880 --> 00:29:35,160
Speaker 2: Yeah, and they're right. Robert Hook found cork, or he

571
00:29:35,240 --> 00:29:39,760
Speaker 2: discovered cells by looking at cork, Yeah, through an early microscope.

572
00:29:39,800 --> 00:29:46,280
Speaker 2: So in this story, sciences hastened by technological advancement lens grinding, yeah,

573
00:29:46,360 --> 00:29:49,400
Speaker 2: and to make microscopes, and then this new technology is

574
00:29:49,520 --> 00:29:51,040
Speaker 2: used to further science, right.

575
00:29:51,120 --> 00:29:55,120
Speaker 1: Yeah, it's like mutual inspiration between Leavin Hook and Hook.

576
00:29:55,920 --> 00:29:56,520
Speaker 1: Leavin Hook.

577
00:29:56,680 --> 00:30:02,520
Speaker 2: Yeah, it was neat because Hook heard about Leavin Hook's microscopes. Yeah,

578
00:30:02,560 --> 00:30:05,640
Speaker 2: got his hands on one or a microscope, looked at

579
00:30:05,720 --> 00:30:08,360
Speaker 2: him like a cork, and said, oh, there's such a thing

580
00:30:08,360 --> 00:30:11,560
Speaker 2: as cells, right. Leavin Hook said, oh, that's pretty neat.

581
00:30:11,640 --> 00:30:13,760
Speaker 2: Let me try. And he said, oh, there's such a

582
00:30:13,800 --> 00:30:18,440
Speaker 2: thing as quote little animals, right, which we call protozoan bacteria. Yeah,

583
00:30:18,480 --> 00:30:22,040
Speaker 2: and one of the Royal Societies. After Leaving Hook presented

584
00:30:22,040 --> 00:30:25,640
Speaker 2: his findings, turned back to Hook and said, hey, Hook,

585
00:30:25,680 --> 00:30:27,640
Speaker 2: we know you're pretty handy with the microscope. Yeah, he

586
00:30:27,800 --> 00:30:31,720
Speaker 2: confirmed leaving Hook's findings are their little animals. Hook said

587
00:30:32,560 --> 00:30:35,880
Speaker 2: there are, indeed, I can see them with my microscope.

588
00:30:35,280 --> 00:30:38,880
Speaker 1: That's right. And that inspired a German botanist name Mattias

589
00:30:39,000 --> 00:30:43,360
Speaker 1: Schleiden to look at a lot of plants and he

590
00:30:43,600 --> 00:30:46,240
Speaker 1: was the first guy to say, you know what, plants

591
00:30:46,240 --> 00:30:48,440
Speaker 1: are composed of cells. And he was having dinner one

592
00:30:48,520 --> 00:30:50,560
Speaker 1: night with his zoologist buddy.

593
00:30:50,640 --> 00:30:52,640
Speaker 2: Yeah, and this is about one hundred years later.

594
00:30:52,760 --> 00:30:57,640
Speaker 1: Yeah, Theodore schwan and said, you know what, dude, order

595
00:30:57,760 --> 00:31:01,400
Speaker 1: the wine and order the ste trust me because this

596
00:31:01,480 --> 00:31:06,560
Speaker 1: place is fantastic. And also, plants are made of cells.

597
00:31:06,680 --> 00:31:09,040
Speaker 1: Don't tell anyone. And he went, you know what, dude,

598
00:31:09,160 --> 00:31:12,760
Speaker 1: I have been investigating animals with microscopes and they're made

599
00:31:12,800 --> 00:31:13,440
Speaker 1: of cells too.

600
00:31:13,760 --> 00:31:16,400
Speaker 2: And so they figured out at this dinner, yeah, that

601
00:31:16,560 --> 00:31:18,920
Speaker 2: everything is made of sales, all living things are made

602
00:31:18,960 --> 00:31:19,560
Speaker 2: of cells.

603
00:31:19,760 --> 00:31:20,200
Speaker 1: Boom.

604
00:31:20,280 --> 00:31:23,400
Speaker 2: Okay, so this is huge. This is a big advancement, right, Yeah,

605
00:31:23,680 --> 00:31:27,080
Speaker 2: we're hitting upon right now. Huge, but it laid the

606
00:31:27,160 --> 00:31:31,640
Speaker 2: further foundation, right, So initial scientific inquiry led to further

607
00:31:31,720 --> 00:31:37,680
Speaker 2: scientific inquiry and further scientific conclusions and generalizations All living

608
00:31:37,720 --> 00:31:41,720
Speaker 2: things are made of cells, and then it was extrapolated elsewhere. Right.

609
00:31:41,800 --> 00:31:46,239
Speaker 1: Yeah, Like twenty years later, Rudolph Virtual said, you know what,

610
00:31:46,360 --> 00:31:49,760
Speaker 1: not only is everything made of living cells, but they

611
00:31:50,000 --> 00:31:53,280
Speaker 1: all come from pre existing cells, which was a huge

612
00:31:53,280 --> 00:31:56,880
Speaker 1: deal at the time because people believed in spontaneous generation.

613
00:31:57,200 --> 00:32:01,000
Speaker 2: Yeah. At the time, like if you left some wheat

614
00:32:01,000 --> 00:32:04,080
Speaker 2: seed in a sweaty shirt, it would spawn mice. I

615
00:32:04,120 --> 00:32:06,840
Speaker 2: think was one of them. Gross, there's a lot of

616
00:32:06,880 --> 00:32:10,160
Speaker 2: weird ones. Press basil between some bricks and you'll get

617
00:32:10,160 --> 00:32:13,800
Speaker 2: a scorpion. Was one, like they were really out there?

618
00:32:14,040 --> 00:32:16,560
Speaker 1: Yeah, well the one that is well not true. But

619
00:32:16,600 --> 00:32:19,600
Speaker 1: the one that you could actually see was rotten meat

620
00:32:19,640 --> 00:32:22,200
Speaker 1: would eventually spawn maggots.

621
00:32:22,280 --> 00:32:23,880
Speaker 2: Right, how did they possibly get there?

622
00:32:24,000 --> 00:32:25,480
Speaker 1: Yeah, spontaneous generation.

623
00:32:25,640 --> 00:32:28,440
Speaker 2: But that's the obvious explanation, and if you think about it,

624
00:32:28,480 --> 00:32:31,720
Speaker 2: they're working from Okham's razor. An Okham's razor says, the

625
00:32:31,760 --> 00:32:36,480
Speaker 2: simplest explanation is usually the right one. Yeah, all other

626
00:32:36,520 --> 00:32:39,480
Speaker 2: things given. Well, the thing is is spontaneous generation has

627
00:32:39,520 --> 00:32:42,800
Speaker 2: never been shown to be possible. Right, if we've got

628
00:32:42,800 --> 00:32:46,800
Speaker 2: the cell thing over here, let's investigate that. So this

629
00:32:47,360 --> 00:32:50,959
Speaker 2: what was the guy's name, Virchow? Yes, he's saying, okay,

630
00:32:51,040 --> 00:32:53,640
Speaker 2: well wait a minute, I've got this cell theory I'm

631
00:32:53,640 --> 00:32:55,880
Speaker 2: working on that's been around for a couple of decades.

632
00:32:56,160 --> 00:32:59,640
Speaker 2: Hypothesis probably cell hypothesis at the nice catch.

633
00:32:59,720 --> 00:33:01,920
Speaker 1: Don't feel bad though, because this article that you sent

634
00:33:02,000 --> 00:33:06,960
Speaker 1: said that scientists today like still like confuse those terms, Yeah,

635
00:33:07,200 --> 00:33:08,240
Speaker 1: just colloquially.

636
00:33:08,400 --> 00:33:10,760
Speaker 2: And the House Stiff Works article makes a good point

637
00:33:10,760 --> 00:33:13,080
Speaker 2: in saying that science and everything that has to do

638
00:33:13,160 --> 00:33:16,280
Speaker 2: with it is in the scientific method is very fluid, Yeah,

639
00:33:16,320 --> 00:33:20,920
Speaker 2: and open new interpretation and experimentation. Yeah, obviously. But so

640
00:33:21,080 --> 00:33:24,840
Speaker 2: he says, Okay, this cell hypothesis, this is a pretty

641
00:33:24,840 --> 00:33:30,400
Speaker 2: good explanation for what we now call spontaneous generation. He

642
00:33:30,400 --> 00:33:33,680
Speaker 2: didn't do anything about it. He just put it out there. Yeah,

643
00:33:33,720 --> 00:33:36,760
Speaker 2: and then along comes Louis Pasteur, who does do something

644
00:33:36,760 --> 00:33:40,120
Speaker 2: about it. He figures out a great experiment to try

645
00:33:40,160 --> 00:33:42,640
Speaker 2: to disprove spontaneous generation.

646
00:33:43,320 --> 00:33:47,160
Speaker 1: Yeah, it's pretty simple too. He basically took a broth,

647
00:33:48,800 --> 00:33:52,120
Speaker 1: put equal amounts in two different beakers. One had a

648
00:33:52,120 --> 00:33:54,840
Speaker 1: straight neck and one had an S shaped neck. He

649
00:33:55,280 --> 00:33:57,920
Speaker 1: boiled it just to make sure everything in it was killed, yea,

650
00:33:58,120 --> 00:33:59,800
Speaker 1: and then just let it sit there in the same

651
00:33:59,840 --> 00:34:03,680
Speaker 1: can conditions, open to the to the world and or

652
00:34:03,720 --> 00:34:06,440
Speaker 1: open to the room like it wasn't corked. In other words,

653
00:34:07,080 --> 00:34:09,960
Speaker 1: no court. He noticed that the one with the straight

654
00:34:10,040 --> 00:34:13,840
Speaker 1: neck eventually became cloudy and discolored, meaning there was some

655
00:34:13,920 --> 00:34:16,120
Speaker 1: junk growing in there. Yeah, and the one in the

656
00:34:16,160 --> 00:34:19,799
Speaker 1: S shape neck did not do anything. It remained the same, right,

657
00:34:20,360 --> 00:34:21,719
Speaker 1: So it led him to think.

658
00:34:21,560 --> 00:34:24,719
Speaker 2: What, well, he thought that germs, that there were such

659
00:34:24,760 --> 00:34:28,759
Speaker 2: thing as germs which leaving hook and hook had already shown. Yeah,

660
00:34:29,800 --> 00:34:33,520
Speaker 2: and that if that in the S shaped flask they

661
00:34:33,560 --> 00:34:37,640
Speaker 2: had gotten trapped in the neck, in this the open neck,

662
00:34:37,960 --> 00:34:41,240
Speaker 2: they had been able to just enter unobstructed and had

663
00:34:41,600 --> 00:34:44,799
Speaker 2: generated there. The reason that the S shape flask was

664
00:34:44,840 --> 00:34:47,960
Speaker 2: still sterile was because there is no such thing as

665
00:34:48,000 --> 00:34:51,759
Speaker 2: spontaneous generation. If there were, then no S shaped neck

666
00:34:51,800 --> 00:34:53,759
Speaker 2: would impede anything like that.

667
00:34:54,440 --> 00:34:55,839
Speaker 1: And boom, there you have it.

668
00:34:56,040 --> 00:35:01,120
Speaker 2: So he disproved that spontaneous generation is a thing.

669
00:35:01,080 --> 00:35:04,800
Speaker 1: Right, that's right through the scientific myth exactly.

670
00:35:05,200 --> 00:35:07,759
Speaker 2: Here's the leap that a lot of people make, scientists

671
00:35:07,760 --> 00:35:11,279
Speaker 2: included that really is a great disservice to science. He

672
00:35:11,440 --> 00:35:15,919
Speaker 2: didn't prove cell theory, right. What he did was take

673
00:35:15,960 --> 00:35:23,480
Speaker 2: that cell hypothesis and present some really persuasive evidence that

674
00:35:23,560 --> 00:35:24,680
Speaker 2: it's probably right.

675
00:35:25,400 --> 00:35:28,120
Speaker 1: Yeah. But like this article you sent points out, disproving

676
00:35:28,160 --> 00:35:30,200
Speaker 1: something is just as important as proving something.

677
00:35:30,400 --> 00:35:32,680
Speaker 2: So here's the thing that's the most you can hope

678
00:35:32,719 --> 00:35:36,080
Speaker 2: for with science is disproving sure with science, unless you're

679
00:35:36,120 --> 00:35:39,160
Speaker 2: talking about math. With science, there's no such thing as proof.

680
00:35:39,760 --> 00:35:43,000
Speaker 2: A theory, even a law, a universal law, still has

681
00:35:43,040 --> 00:35:47,040
Speaker 2: the potential for being undermined by one single experiment, one

682
00:35:47,080 --> 00:35:52,040
Speaker 2: single observation, and therefore there is no real ultimate proof

683
00:35:52,320 --> 00:35:56,600
Speaker 2: In science. There's just theories and support for theories, and

684
00:35:56,600 --> 00:36:01,799
Speaker 2: then ultimately laws and further and further support for laws, right,

685
00:36:02,239 --> 00:36:07,800
Speaker 2: but they're not proven. What science does ultimately is disprove

686
00:36:07,880 --> 00:36:12,840
Speaker 2: things or lend support for existing theories or existing interpretations

687
00:36:12,840 --> 00:36:15,719
Speaker 2: of why things happen the way they do. Yeah, and

688
00:36:15,760 --> 00:36:18,320
Speaker 2: that's what Pasture did. So if you look at that experiment,

689
00:36:18,600 --> 00:36:23,120
Speaker 2: he disproved spontaneous generation, but he lent support to the

690
00:36:23,200 --> 00:36:25,879
Speaker 2: cell theory, and probably with his experiment it went from

691
00:36:25,880 --> 00:36:28,680
Speaker 2: the cell hypothesis to the cell theory, right, because it

692
00:36:28,719 --> 00:36:32,120
Speaker 2: was just so persuasive. And that's what a theory is.

693
00:36:32,160 --> 00:36:34,239
Speaker 2: It means that a lot of people out there who

694
00:36:34,239 --> 00:36:38,919
Speaker 2: are reasonable say this explanation is probably the right one.

695
00:36:39,000 --> 00:36:40,879
Speaker 1: Yeah, it's predictive. If you do it over and over,

696
00:36:40,960 --> 00:36:42,759
Speaker 1: you're probably going to get the same result. Right.

697
00:36:43,280 --> 00:36:46,920
Speaker 2: But that's not to say that Pastures showed that if

698
00:36:46,920 --> 00:36:50,640
Speaker 2: you do this a million and one times that the

699
00:36:51,080 --> 00:36:54,520
Speaker 2: s shaped flask won't turn cloudy. Yeah, he didn't prove that.

700
00:36:54,880 --> 00:36:58,800
Speaker 2: You can't prove that, which is again science can disprove

701
00:36:59,040 --> 00:37:00,520
Speaker 2: and lend support can't prove.

702
00:37:00,960 --> 00:37:04,000
Speaker 1: Very good point. So right after this message break, we're

703
00:37:04,000 --> 00:37:06,560
Speaker 1: going to get into the actual steps of the scientific method.

704
00:37:19,360 --> 00:37:22,279
Speaker 1: All right, dude, I guess at long last we're there.

705
00:37:23,040 --> 00:37:26,960
Speaker 1: Like you mentioned before, the scientific method is fluid, and

706
00:37:27,080 --> 00:37:30,440
Speaker 1: it's not like when you get your science degree they

707
00:37:30,440 --> 00:37:34,040
Speaker 1: hand you a little laminated card like the Miranda rights

708
00:37:34,120 --> 00:37:37,200
Speaker 1: that cops carry that you know, list out all the

709
00:37:37,200 --> 00:37:41,319
Speaker 1: different steps you have to take. But generally maybe.

710
00:37:41,160 --> 00:37:43,879
Speaker 2: Yeah, I would we should carry those around.

711
00:37:43,920 --> 00:37:44,160
Speaker 1: All right.

712
00:37:44,160 --> 00:37:46,480
Speaker 2: We should make little wallet cars of the scientific method

713
00:37:46,560 --> 00:37:49,160
Speaker 2: just to carry stuff you should know logo on it.

714
00:37:49,239 --> 00:37:51,040
Speaker 2: Oh yeah, I'll make a million bucks.

715
00:37:50,840 --> 00:37:51,640
Speaker 1: Brand them and sell them.

716
00:37:51,719 --> 00:37:54,040
Speaker 2: Yeah.

717
00:37:54,239 --> 00:37:57,640
Speaker 1: Generally speaking, though, it follows these steps. The first thing

718
00:37:57,640 --> 00:37:59,960
Speaker 1: you do, like we mentioned earlier, is you observe something.

719
00:38:00,520 --> 00:38:05,080
Speaker 1: You ask a question next, Like Darwin was known, I

720
00:38:05,080 --> 00:38:07,400
Speaker 1: think when we did our podcast on him to he

721
00:38:07,400 --> 00:38:11,400
Speaker 1: would spend like a week on three square feet of ground.

722
00:38:12,520 --> 00:38:13,680
Speaker 2: It was like even longer than that.

723
00:38:13,760 --> 00:38:15,239
Speaker 1: Remember it was, wasn't it.

724
00:38:15,160 --> 00:38:17,280
Speaker 2: He said that he didn't he wasn't gonna Moe's lawn

725
00:38:17,320 --> 00:38:20,320
Speaker 2: for like three years because he wanted to see what happened.

726
00:38:20,600 --> 00:38:24,440
Speaker 1: Yeah, so he's the ultimate and qualitative data of just observing,

727
00:38:24,920 --> 00:38:28,279
Speaker 1: writing things down, and asking questions. And the reason you

728
00:38:28,320 --> 00:38:32,120
Speaker 1: ask your question is so you can narrow something down

729
00:38:32,960 --> 00:38:34,600
Speaker 1: like that. I think the example they use in here

730
00:38:34,719 --> 00:38:38,720
Speaker 1: is on Galapagos, like the beaks of what bird?

731
00:38:38,800 --> 00:38:39,520
Speaker 2: Was it? Finches?

732
00:38:39,640 --> 00:38:41,800
Speaker 1: Yeah, the finch bird. He noticed a bunch of different beaks,

733
00:38:42,360 --> 00:38:45,279
Speaker 1: so he finally posed a question, like, you know, I

734
00:38:45,320 --> 00:38:48,120
Speaker 1: think these beaks are different for a very specific reason,

735
00:38:48,520 --> 00:38:49,759
Speaker 1: and I aim to find out why.

736
00:38:50,160 --> 00:38:55,200
Speaker 2: Yes, he said, what caused the diversification of finches on Galapagos? Who?

737
00:38:56,640 --> 00:38:57,960
Speaker 1: You should have done that with an accent?

738
00:38:58,920 --> 00:39:01,920
Speaker 2: Well, yeah, he would have had a ritorse acent huh yeah, huh.

739
00:39:01,719 --> 00:39:03,479
Speaker 1: Unless he was pretending to be someone else.

740
00:39:03,840 --> 00:39:06,759
Speaker 2: I always think of him as like sounding like Hemingway

741
00:39:06,840 --> 00:39:07,280
Speaker 2: or something.

742
00:39:07,680 --> 00:39:10,120
Speaker 1: Oh yeah, just drunk and violent kind of.

743
00:39:10,800 --> 00:39:12,640
Speaker 2: But he wasn't. He was like the opposite of that.

744
00:39:13,239 --> 00:39:15,920
Speaker 1: Yeah, well I saw that the movie, so I picture

745
00:39:16,000 --> 00:39:20,560
Speaker 1: his voice as the dude that played him who I.

746
00:39:20,480 --> 00:39:22,520
Speaker 2: Can't remember right now, ed Norton.

747
00:39:22,880 --> 00:39:28,680
Speaker 1: No, I finally saw Birdman though, do you see that? Yeah? Yeah,

748
00:39:29,000 --> 00:39:30,680
Speaker 1: great movie.

749
00:39:30,960 --> 00:39:31,680
Speaker 2: I disagree.

750
00:39:31,719 --> 00:39:32,400
Speaker 1: Oh you didn't like it?

751
00:39:32,880 --> 00:39:33,200
Speaker 2: What?

752
00:39:34,320 --> 00:39:39,799
Speaker 1: Wow? That surprises me. We'll get into that off air.

753
00:39:41,280 --> 00:39:44,279
Speaker 1: So uh sorry, you just threw me with that.

754
00:39:44,640 --> 00:39:47,920
Speaker 2: Make an observation. Yes, he's ungalopaghost and he's like, what

755
00:39:48,040 --> 00:39:50,400
Speaker 2: the heck's with all these different finches? It's one small island.

756
00:39:50,719 --> 00:39:53,640
Speaker 2: Why would there be different species of finch? So ask

757
00:39:54,080 --> 00:39:58,120
Speaker 2: and why are they all seeming to survive and coexist?

758
00:39:58,239 --> 00:40:01,800
Speaker 2: So well, what's what? Yeah? Then he leads to the

759
00:40:01,880 --> 00:40:05,960
Speaker 2: question what's making all of these species of finches so diverse?

760
00:40:06,400 --> 00:40:09,439
Speaker 1: Right? Or Bill Harris uses a pretty good example. That's

761
00:40:09,680 --> 00:40:13,880
Speaker 1: something everyone can understand, like what car body shape is

762
00:40:13,920 --> 00:40:17,120
Speaker 1: the best for air resistance? Like one the shape like

763
00:40:17,160 --> 00:40:20,040
Speaker 1: a box, or one the shape like aerodynamic like a bird. Right,

764
00:40:20,239 --> 00:40:22,759
Speaker 1: And he carries that out In the next step. You

765
00:40:22,840 --> 00:40:28,640
Speaker 1: formulate your hypothesis based on your you know, fore knowledge

766
00:40:28,680 --> 00:40:32,040
Speaker 1: and maybe observations like so, you know what, I think

767
00:40:32,640 --> 00:40:34,600
Speaker 1: that a car shaped like a bird is probably more

768
00:40:34,640 --> 00:40:36,320
Speaker 1: aerodynamic than one shape like a box.

769
00:40:36,400 --> 00:40:38,080
Speaker 2: Yeah. If you're thinking, if you're the type of person

770
00:40:38,120 --> 00:40:41,880
Speaker 2: who's sitting around asking questions about aerodynamics, you probably already

771
00:40:41,960 --> 00:40:44,759
Speaker 2: have some sort of sense that a box is less

772
00:40:44,800 --> 00:40:46,080
Speaker 2: aerodynamic than a bird.

773
00:40:46,160 --> 00:40:46,520
Speaker 1: That's right.

774
00:40:46,640 --> 00:40:49,879
Speaker 2: Boxes rarely fly unless they're carried by one of those

775
00:40:49,920 --> 00:40:51,680
Speaker 2: delightful Amazon delivery drones.

776
00:40:54,200 --> 00:40:55,840
Speaker 1: They don't have those yet, right, They're not gonna do that,

777
00:40:55,880 --> 00:40:56,200
Speaker 1: are they.

778
00:40:57,239 --> 00:41:01,759
Speaker 2: There's like a pizza delivery drone service, man, I think

779
00:41:01,800 --> 00:41:05,680
Speaker 2: where you No, it's pizza grilled cheese in New York

780
00:41:05,760 --> 00:41:07,960
Speaker 2: and you go stand on an ax after you order

781
00:41:08,000 --> 00:41:09,520
Speaker 2: and it like comes and drops it.

782
00:41:09,640 --> 00:41:12,319
Speaker 1: That is the dumbest thing of error. And I can't

783
00:41:12,320 --> 00:41:13,000
Speaker 1: wait to do it.

784
00:41:13,320 --> 00:41:14,640
Speaker 2: But they're making a lot of money.

785
00:41:15,640 --> 00:41:18,400
Speaker 1: That's pretty funny. Yeah, we can't get food to the

786
00:41:18,400 --> 00:41:21,040
Speaker 1: homeless somehow, exactly, we can drop a grilled cheese on

787
00:41:21,040 --> 00:41:21,560
Speaker 1: someone's head.

788
00:41:22,000 --> 00:41:24,840
Speaker 2: They're like, you homeless, get off of that x exactly.

789
00:41:26,480 --> 00:41:29,120
Speaker 1: All right. So your hypothesis I don't think we ever

790
00:41:29,160 --> 00:41:33,040
Speaker 1: mentioned is typically represented as an if then statement.

791
00:41:33,160 --> 00:41:35,479
Speaker 2: Yeah, if you're doing good science, Yeah, like.

792
00:41:35,440 --> 00:41:42,719
Speaker 1: If the car's profile, well the example he uses if

793
00:41:42,760 --> 00:41:45,880
Speaker 1: the body's profile related to the amount of air it produces,

794
00:41:46,640 --> 00:41:48,000
Speaker 1: which is the more general statement.

795
00:41:48,080 --> 00:41:49,760
Speaker 2: Yeah, that's like based on a theory.

796
00:41:49,880 --> 00:41:51,960
Speaker 1: Yeah, and it's going to get more specific then the

797
00:41:52,000 --> 00:41:54,080
Speaker 1: car design, like the body of a bird will be

798
00:41:54,120 --> 00:41:56,720
Speaker 1: more aerodynamic than one like a box.

799
00:41:57,000 --> 00:42:00,160
Speaker 2: So that's inductive reasoning, starting with the broad statement and

800
00:42:00,239 --> 00:42:01,799
Speaker 2: going to something narrow.

801
00:42:01,800 --> 00:42:03,840
Speaker 1: And it's if. Then at the same time.

802
00:42:04,080 --> 00:42:06,680
Speaker 2: Yeah, and now you have a test. You have a

803
00:42:06,760 --> 00:42:08,800
Speaker 2: question that can be answered, you can figure out a

804
00:42:08,800 --> 00:42:09,520
Speaker 2: way to answer it.

805
00:42:09,760 --> 00:42:12,320
Speaker 1: Yeah, And he points out too, this is pretty important

806
00:42:12,360 --> 00:42:16,680
Speaker 1: that your hypothesis, if it's formulated correctly, means that it's

807
00:42:16,680 --> 00:42:19,360
Speaker 1: testable and it's falsifiable.

808
00:42:19,040 --> 00:42:22,880
Speaker 2: Which are often one and the same true, you know. Yeah,

809
00:42:22,920 --> 00:42:25,680
Speaker 2: And that's again we go to the people who say

810
00:42:25,719 --> 00:42:31,520
Speaker 2: that their soft sciences aren't real science, they're pseudoscience because

811
00:42:31,800 --> 00:42:34,160
Speaker 2: a lot of the data that they come up with,

812
00:42:34,200 --> 00:42:37,600
Speaker 2: a lot of the hypotheses they come up with aren't falsifiable,

813
00:42:37,600 --> 00:42:41,640
Speaker 2: they're not testable. Right, it's a thing, it's an issue,

814
00:42:41,920 --> 00:42:42,480
Speaker 2: it's a thing.

815
00:42:43,280 --> 00:42:46,560
Speaker 1: So next up in the steps, you're going to experiment.

816
00:42:47,320 --> 00:42:50,000
Speaker 1: And when you experiment, you can't just go in there

817
00:42:50,000 --> 00:42:52,560
Speaker 1: Willie Nelly and do whatever you want. You have to

818
00:42:52,560 --> 00:42:56,279
Speaker 1: set up specific conditions and they must be controlled. That's

819
00:42:56,400 --> 00:42:56,719
Speaker 1: the key.

820
00:42:56,920 --> 00:42:59,640
Speaker 2: And you want to everything that's supposed to be identical

821
00:42:59,760 --> 00:43:03,279
Speaker 2: need to be identical. So basically you have two variables.

822
00:43:03,320 --> 00:43:06,239
Speaker 2: At least you have an independent variable, yes, and you

823
00:43:06,280 --> 00:43:11,120
Speaker 2: have a dependent variable. And if you're talking about car shape,

824
00:43:11,360 --> 00:43:13,680
Speaker 2: that is the independent variable in this study.

825
00:43:13,800 --> 00:43:16,480
Speaker 1: Yeah, that's the one that's manipulated.

826
00:43:15,960 --> 00:43:19,160
Speaker 2: Exactly, it's the one you're controlling. The independent variable is

827
00:43:19,239 --> 00:43:22,640
Speaker 2: the one you, the researcher, is controlling. So in this case,

828
00:43:22,920 --> 00:43:26,200
Speaker 2: you're controlling the shape of the car. You have yourself

829
00:43:26,239 --> 00:43:29,040
Speaker 2: a bird shape car and you have yourself a box

830
00:43:29,080 --> 00:43:32,240
Speaker 2: shaped car. So the shape of the car changed because

831
00:43:32,320 --> 00:43:34,960
Speaker 2: you made it change. Now when you blast a bunch

832
00:43:35,040 --> 00:43:38,239
Speaker 2: of air over it during your experiment, what you're measuring

833
00:43:38,560 --> 00:43:43,640
Speaker 2: is the dependent variable. So you're measuring what happens based

834
00:43:43,680 --> 00:43:45,000
Speaker 2: on the change that you made.

835
00:43:45,280 --> 00:43:48,960
Speaker 1: That's right, And you want to study one single variable

836
00:43:48,960 --> 00:43:50,520
Speaker 1: at a time, basically.

837
00:43:50,160 --> 00:43:54,480
Speaker 2: Yeah, don't get fancy, just do good science, step by step, methodical.

838
00:43:55,000 --> 00:43:57,920
Speaker 1: You also have to have your control group in any experiment,

839
00:43:58,480 --> 00:44:02,920
Speaker 1: and an experimental group, and the controlled group is what's

840
00:44:02,960 --> 00:44:06,160
Speaker 1: gonna allow you to compare the test results to that

841
00:44:06,239 --> 00:44:09,960
Speaker 1: baseline measurement. Yeah, and you need that baseline measurement, so

842
00:44:10,680 --> 00:44:12,280
Speaker 1: it's not just like chance.

843
00:44:12,400 --> 00:44:15,520
Speaker 2: Basically, exactly, like if Pasture had just done the S

844
00:44:15,520 --> 00:44:19,040
Speaker 2: shaped neck and nothing happened. Right, he wouldn't have necessarily

845
00:44:19,560 --> 00:44:21,879
Speaker 2: been able to say that he was right even though

846
00:44:21,920 --> 00:44:24,960
Speaker 2: he was right. He needed that control, which was the

847
00:44:25,120 --> 00:44:26,600
Speaker 2: open flask, right.

848
00:44:26,800 --> 00:44:29,080
Speaker 1: Or with the cars, you need two cars, like you said,

849
00:44:29,520 --> 00:44:31,759
Speaker 1: one bird shaped and one box shaped.

850
00:44:31,640 --> 00:44:33,960
Speaker 2: Right, Or then maybe in this case, since the bird

851
00:44:33,960 --> 00:44:36,120
Speaker 2: shape and the box shape both show up in the hypothsis,

852
00:44:36,120 --> 00:44:39,120
Speaker 2: you'd need a third like egg shaped one or something

853
00:44:39,239 --> 00:44:39,600
Speaker 2: like that.

854
00:44:39,840 --> 00:44:41,520
Speaker 1: Oh, I bet that would be pretty streamlined.

855
00:44:42,600 --> 00:44:44,320
Speaker 2: Yeah, yeah, yeah.

856
00:44:44,360 --> 00:44:47,080
Speaker 1: But the key though, is all of those variables have

857
00:44:47,200 --> 00:44:49,560
Speaker 1: to be All the other variables have to be the same,

858
00:44:50,200 --> 00:44:52,080
Speaker 1: like you have to have them. They have to be

859
00:44:52,120 --> 00:44:54,040
Speaker 1: the same weight, they have to be painted the same,

860
00:44:55,080 --> 00:44:58,640
Speaker 1: the tires, everything, the windows. One can't have an antenna

861
00:44:58,680 --> 00:45:00,600
Speaker 1: on the other, knot. They've all they got to be

862
00:45:00,640 --> 00:45:02,960
Speaker 1: identical other than the one variable.

863
00:45:02,640 --> 00:45:05,480
Speaker 2: Right, the independent variable that you're that's the one you

864
00:45:05,520 --> 00:45:07,960
Speaker 2: want different. Everything else you want the same or else

865
00:45:08,040 --> 00:45:11,480
Speaker 2: as possible that Oh well, this one had bigger tires,

866
00:45:11,520 --> 00:45:13,880
Speaker 2: so that actually made it more aerodynamic.

867
00:45:14,000 --> 00:45:16,160
Speaker 1: Yeah, and you're just doing yourself a favor by doing

868
00:45:16,200 --> 00:45:18,279
Speaker 1: all that stuff. Yeah, you know, you want to rule

869
00:45:18,280 --> 00:45:20,120
Speaker 1: out everything else but that one variable.

870
00:45:20,200 --> 00:45:20,399
Speaker 2: Yep.

871
00:45:21,880 --> 00:45:25,880
Speaker 1: After that you want to analyze your data so you

872
00:45:25,880 --> 00:45:30,640
Speaker 1: can draw your conclusion. And sometimes it's kind of straightforward

873
00:45:30,680 --> 00:45:33,200
Speaker 1: and easy. Sometimes takes a lot of work and a

874
00:45:33,239 --> 00:45:36,439
Speaker 1: lot of various tools. Yes, draw it out.

875
00:45:36,600 --> 00:45:40,800
Speaker 2: Let's say you're just blasting a car in a wind tunnel. Yeah,

876
00:45:40,880 --> 00:45:44,920
Speaker 2: you're measuring the wind resistance using certain awesome instruments and

877
00:45:44,960 --> 00:45:47,600
Speaker 2: that kind of stuff, and you're taking that data, and

878
00:45:47,640 --> 00:45:49,719
Speaker 2: then afterward you're going to analyze it. You're going to

879
00:45:49,800 --> 00:45:53,240
Speaker 2: compare the data that you gathered from the bird shaped

880
00:45:53,280 --> 00:45:56,239
Speaker 2: car the box shaped car, and then the control the

881
00:45:56,280 --> 00:45:58,239
Speaker 2: egg shaped car. Right, You're going to compare them, and

882
00:45:58,280 --> 00:46:01,160
Speaker 2: you're going to say, well, the wind resistance was less

883
00:46:01,719 --> 00:46:05,120
Speaker 2: for the bird shaped car than the box shaped car,

884
00:46:05,200 --> 00:46:09,600
Speaker 2: which means that my hypothesis was correct.

885
00:46:09,280 --> 00:46:11,880
Speaker 1: Right, and here all the data points, whereas Louis pasteor

886
00:46:11,920 --> 00:46:14,640
Speaker 1: could just say, look at the beakers exactly.

887
00:46:15,160 --> 00:46:17,960
Speaker 2: Don't be an idiot. Yeah, I'm a scientist.

888
00:46:18,040 --> 00:46:22,000
Speaker 1: That one's got gross stuff. You can see it, right.

889
00:46:22,080 --> 00:46:25,799
Speaker 2: But the other thing about science, too, Chuck, ideally, is

890
00:46:25,880 --> 00:46:29,360
Speaker 2: let's say that egg shaped one turned out the control

891
00:46:29,400 --> 00:46:33,040
Speaker 2: group turned out to have better wind resistance than anything. Well,

892
00:46:33,080 --> 00:46:36,000
Speaker 2: just by virtue of carrying out this experiment correctly, you

893
00:46:36,000 --> 00:46:40,160
Speaker 2: would have stumbled upon an even better aerodynamic design, and

894
00:46:40,200 --> 00:46:42,880
Speaker 2: you would have come up with that little egg shaped

895
00:46:42,880 --> 00:46:45,719
Speaker 2: Mercedes suv. Yeah, that was so huge, just like ten

896
00:46:45,800 --> 00:46:46,520
Speaker 2: years ago.

897
00:46:46,560 --> 00:46:49,680
Speaker 1: The Mercedes egg right coming to a store near you.

898
00:46:50,080 --> 00:46:53,880
Speaker 2: So that's a big, big part of the scientific method

899
00:46:54,000 --> 00:47:02,279
Speaker 2: is carrying out a an experiment, control the variables, analyzing

900
00:47:02,320 --> 00:47:05,360
Speaker 2: the data. And then there's a step that he missed

901
00:47:05,360 --> 00:47:09,360
Speaker 2: that is very rarely part of a scientific method list.

902
00:47:09,560 --> 00:47:12,800
Speaker 2: Oh yeah, that is to share your data. Oh sure,

903
00:47:12,840 --> 00:47:15,520
Speaker 2: and this is a huge problem with science right now.

904
00:47:15,760 --> 00:47:18,759
Speaker 1: Yeah, the article you sent was really eye opening. Scientific

905
00:47:18,800 --> 00:47:21,360
Speaker 1: research has changed the world. Now it needs to change itself.

906
00:47:21,440 --> 00:47:24,080
Speaker 2: Yeah, it's an economist article. It's up on the internet.

907
00:47:24,200 --> 00:47:28,240
Speaker 1: Yeah, it was kind of scary that it's I mean,

908
00:47:28,400 --> 00:47:31,000
Speaker 1: here's some of the data he points out is one

909
00:47:31,040 --> 00:47:35,320
Speaker 1: rule of thumb among biotech venture capitalists is about half

910
00:47:35,680 --> 00:47:39,719
Speaker 1: fifty percent of published research can't even be replicated. And

911
00:47:39,719 --> 00:47:43,160
Speaker 1: a biotech firm, Amjin, found that they could reproduce only

912
00:47:43,239 --> 00:47:46,880
Speaker 1: six of their fifty three landmark studies in cancer research.

913
00:47:47,440 --> 00:47:50,960
Speaker 1: So you can't repeat these things. It's like everyone's fighting

914
00:47:51,000 --> 00:47:54,440
Speaker 1: for dollars in fame, and maybe not fame, but to

915
00:47:54,520 --> 00:47:57,919
Speaker 1: some of our career advancement, sure such that they're kind

916
00:47:57,920 --> 00:47:59,960
Speaker 1: of not doing that final step any longer.

917
00:48:00,280 --> 00:48:03,919
Speaker 2: No, and it's not necessarily just them, it's the other

918
00:48:04,080 --> 00:48:07,360
Speaker 2: scientists aren't going back and saying, well, let me see

919
00:48:07,520 --> 00:48:11,200
Speaker 2: if your results are reproducible. People are just taking it

920
00:48:11,239 --> 00:48:14,520
Speaker 2: on faith. We need another Roger Bacon to come along

921
00:48:14,520 --> 00:48:17,120
Speaker 2: and be like, dude, we can't just blindly accept that

922
00:48:17,320 --> 00:48:20,400
Speaker 2: one person carried out this one study and then just

923
00:48:20,480 --> 00:48:23,799
Speaker 2: go do clinical trials on it without anybody reproducing it

924
00:48:23,840 --> 00:48:27,600
Speaker 2: to see if the results can be verified independently.

925
00:48:27,760 --> 00:48:30,520
Speaker 1: Yeah, because, and this is a good time to mention bias.

926
00:48:30,560 --> 00:48:33,600
Speaker 1: There is such a thing as bias, and it still happens.

927
00:48:34,719 --> 00:48:40,040
Speaker 1: A scientist is usually out to prove something or disprove

928
00:48:40,120 --> 00:48:44,719
Speaker 1: something that they want a specific result. Like even if

929
00:48:44,760 --> 00:48:48,759
Speaker 1: you're super open minded, you're probably hoping to disprove or

930
00:48:48,800 --> 00:48:52,480
Speaker 1: prove something one way or the other, and your confirmation

931
00:48:52,600 --> 00:48:55,319
Speaker 1: bias might you know, even if you don't think you're

932
00:48:55,320 --> 00:48:58,399
Speaker 1: doing it, you might nudge out some results that don't

933
00:48:58,400 --> 00:49:01,600
Speaker 1: support your hypothesis, and so you won't make it into

934
00:49:01,680 --> 00:49:07,719
Speaker 1: that awesome journal which this author points out that journals

935
00:49:07,760 --> 00:49:13,800
Speaker 1: need to start putting in what he calls uninteresting results

936
00:49:13,800 --> 00:49:17,520
Speaker 1: in experiments, right, or like the stuff that's not sexy, right, or.

937
00:49:17,560 --> 00:49:21,720
Speaker 2: Studies that failed to show that their hypothesis was correct.

938
00:49:21,840 --> 00:49:23,000
Speaker 1: Yeah, stuff is disproved.

939
00:49:23,040 --> 00:49:26,359
Speaker 2: Those things still need to well not even disproved. Well, yeah,

940
00:49:26,360 --> 00:49:28,319
Speaker 2: I guess it is disproved. But yes, like the guy

941
00:49:28,360 --> 00:49:32,960
Speaker 2: set out to say, like that a red balloon uses

942
00:49:33,040 --> 00:49:36,279
Speaker 2: less helium than a silver balloon and it turns out

943
00:49:36,280 --> 00:49:38,799
Speaker 2: that no, they use the same amount of helium. Well,

944
00:49:38,880 --> 00:49:42,200
Speaker 2: if that study gets published and put out there into

945
00:49:42,280 --> 00:49:46,040
Speaker 2: the scientific literature on helium and balloons, then it's going

946
00:49:46,120 --> 00:49:49,480
Speaker 2: to prevent some other scientists down the road from wasting time, money,

947
00:49:49,520 --> 00:49:54,400
Speaker 2: and helium, which, as you'll remember, is an increasingly needed commodity.

948
00:49:55,520 --> 00:49:59,880
Speaker 2: By carrying out the same experiment, whether the results are

949
00:50:00,200 --> 00:50:03,080
Speaker 2: positive or negative or what, the study is meant to

950
00:50:03,120 --> 00:50:05,479
Speaker 2: be shared. And that's the point of the scientific method

951
00:50:05,600 --> 00:50:08,279
Speaker 2: is to reduce bias, right, And if you follow it

952
00:50:08,320 --> 00:50:10,920
Speaker 2: all the way through ideally and do all of the steps,

953
00:50:10,920 --> 00:50:15,319
Speaker 2: including share your research whether it's happy or sad, then

954
00:50:15,960 --> 00:50:19,319
Speaker 2: science benefits. The world benefits, and by not doing that,

955
00:50:19,440 --> 00:50:21,160
Speaker 2: the world does not benefit.

956
00:50:21,320 --> 00:50:24,920
Speaker 1: Yeah. He points out that these days only fourteen percent

957
00:50:24,960 --> 00:50:29,799
Speaker 1: of published papers are quote unquote negative results, and it

958
00:50:29,880 --> 00:50:33,680
Speaker 1: used to be like thirty percent or more. And he says,

959
00:50:33,719 --> 00:50:35,160
Speaker 1: because it's a lot of it has to do with

960
00:50:35,239 --> 00:50:40,279
Speaker 1: this sort of you know, getting in these journals and

961
00:50:40,280 --> 00:50:43,040
Speaker 1: you're the rockstar scientist and this study is super sexy.

962
00:50:43,560 --> 00:50:45,319
Speaker 1: Like if they kind of quit going that route and

963
00:50:45,320 --> 00:50:48,759
Speaker 1: made it what it should be, then research dollars would

964
00:50:48,800 --> 00:50:52,480
Speaker 1: be better spent and people could, you know, he said,

965
00:50:52,520 --> 00:50:54,560
Speaker 1: the peer reviewed thing isn't even all it's cracked up.

966
00:50:54,480 --> 00:50:57,120
Speaker 2: To be, I know. He mentions a study from a

967
00:50:57,160 --> 00:51:00,759
Speaker 2: medical journal that gave a bunch of peer reviewers some

968
00:51:00,840 --> 00:51:05,800
Speaker 2: stuff with deliberate errors inserted into the research, into the studies,

969
00:51:06,160 --> 00:51:08,160
Speaker 2: and even when they were told that they were being

970
00:51:08,239 --> 00:51:10,560
Speaker 2: tested to find this, they still missed.

971
00:51:10,320 --> 00:51:11,880
Speaker 1: A lot of it. Yeah.

972
00:51:12,120 --> 00:51:14,680
Speaker 2: So yeah, the science needs to kind of reevaluate the

973
00:51:14,719 --> 00:51:18,360
Speaker 2: way it's carrying out science. It's not science. The problem

974
00:51:19,000 --> 00:51:21,879
Speaker 2: isn't science itself. The problem isn't the scientific method. It's

975
00:51:21,880 --> 00:51:24,040
Speaker 2: the way that it's being used or not followed through.

976
00:51:24,239 --> 00:51:26,040
Speaker 2: And a lot of it has to do with academia

977
00:51:26,080 --> 00:51:27,440
Speaker 2: and the people funding science.

978
00:51:27,640 --> 00:51:29,640
Speaker 1: Yeah, and he said, you know, these days there's up

979
00:51:29,760 --> 00:51:33,360
Speaker 1: seven million researchers, and back in the day, even in

980
00:51:33,440 --> 00:51:36,959
Speaker 1: like the nineteen fifties, there were like a few thousand maybe, right,

981
00:51:37,040 --> 00:51:39,839
Speaker 1: So there's just a lot of career competition, he calls

982
00:51:39,840 --> 00:51:43,600
Speaker 1: it careerism. And so you fake a result or too,

983
00:51:43,719 --> 00:51:46,440
Speaker 1: or you just nudge out some results that don't support

984
00:51:46,440 --> 00:51:50,160
Speaker 1: your hypothesis. Yes, you want the bigger paycheck or the

985
00:51:50,160 --> 00:51:53,360
Speaker 1: fame or notoriety, and all of a sudden, science is

986
00:51:53,440 --> 00:51:58,560
Speaker 1: not science. Yeah, you know, it's pseudoscience exactly.

987
00:51:59,400 --> 00:52:02,120
Speaker 2: And speaking of pseudoscience, I think we've reached the point

988
00:52:02,120 --> 00:52:05,680
Speaker 2: where we should talk about the limitations of the scientific method,

989
00:52:06,080 --> 00:52:09,480
Speaker 2: because it does have its limits, right, like the way

990
00:52:09,520 --> 00:52:11,840
Speaker 2: that the scientific method is set up, especially if you

991
00:52:11,920 --> 00:52:16,520
Speaker 2: go through if you include falsification, which most scientists now

992
00:52:16,600 --> 00:52:21,200
Speaker 2: say is a thing like falsifiability of your hypothesis means

993
00:52:21,239 --> 00:52:24,960
Speaker 2: that you have a real scientific hypothesis the if it

994
00:52:25,000 --> 00:52:28,840
Speaker 2: can be disproven by some observation or some measurement or whatever,

995
00:52:29,040 --> 00:52:32,839
Speaker 2: then it's falsifiable. And if it's not falsifiable, then it's

996
00:52:32,880 --> 00:52:36,960
Speaker 2: not really science. So the thing is for something to

997
00:52:37,000 --> 00:52:39,399
Speaker 2: be falsifiable, and it was actually a philosopher that came

998
00:52:39,480 --> 00:52:42,120
Speaker 2: up with the concept of falsification a guy named Carl

999
00:52:42,160 --> 00:52:45,359
Speaker 2: Popper in the nineteen thirties, and he was the one

1000
00:52:45,360 --> 00:52:48,600
Speaker 2: that said, like, you have to be able to falsify

1001
00:52:48,680 --> 00:52:52,520
Speaker 2: something for it to be disproven or supported, and if not,

1002
00:52:52,600 --> 00:52:56,279
Speaker 2: then it's pseudoscience. Well, part and parcel of that is

1003
00:52:56,320 --> 00:52:58,440
Speaker 2: that what you're saying has to be able to be

1004
00:52:58,560 --> 00:53:03,240
Speaker 2: detected rially, there's some way that has to the presence

1005
00:53:03,280 --> 00:53:06,360
Speaker 2: of it has to be measured or inferred. And so

1006
00:53:06,640 --> 00:53:10,239
Speaker 2: a lot of people say, well, then with the scientific

1007
00:53:10,320 --> 00:53:14,399
Speaker 2: method it reaches the limits of its current usefulness when

1008
00:53:14,400 --> 00:53:18,520
Speaker 2: it tries to explain the supernatural. When somebody says.

1009
00:53:18,120 --> 00:53:20,960
Speaker 1: Like, ghosts are real, exactly.

1010
00:53:20,960 --> 00:53:24,719
Speaker 2: You can't prove that, well, you also can't disprove it either, right,

1011
00:53:25,000 --> 00:53:30,640
Speaker 2: And so if you are a scientist who says, because

1012
00:53:30,719 --> 00:53:34,759
Speaker 2: the scientific method can't prove or disprove the existence of

1013
00:53:34,800 --> 00:53:38,440
Speaker 2: ghosts or God, there is no such thing as ghosts

1014
00:53:38,520 --> 00:53:42,440
Speaker 2: or God, you're making a leap of faith just as

1015
00:53:42,480 --> 00:53:45,359
Speaker 2: much as the same person who says science can't prove

1016
00:53:45,440 --> 00:53:48,720
Speaker 2: or disprove the existence of ghosts or God, therefore God's

1017
00:53:48,760 --> 00:53:52,200
Speaker 2: and ghosts are real. They're both leaps of faith, and

1018
00:53:52,239 --> 00:53:55,880
Speaker 2: that really the most scientific approach to the existence of

1019
00:53:55,920 --> 00:53:59,600
Speaker 2: the supernatural, whether it is ghost or God, is that

1020
00:53:59,640 --> 00:54:03,200
Speaker 2: we see simply don't know, and that we cannot know scientifically.

1021
00:54:03,960 --> 00:54:07,120
Speaker 2: But that doesn't mean that it does exist or doesn't exist, right,

1022
00:54:07,280 --> 00:54:10,160
Speaker 2: And that's saying that science shows that it does or

1023
00:54:10,160 --> 00:54:14,040
Speaker 2: doesn't exist is by definition the opposite of what science shows.

1024
00:54:14,480 --> 00:54:19,600
Speaker 2: Science shows neither. It's not capable of showing or showing

1025
00:54:19,600 --> 00:54:20,840
Speaker 2: that something doesn't exist.

1026
00:54:20,920 --> 00:54:23,920
Speaker 1: Yeah, that's a good point. The other place where science

1027
00:54:23,920 --> 00:54:27,640
Speaker 1: can get corrupted is when it blurs the lines, or

1028
00:54:27,680 --> 00:54:32,520
Speaker 1: when people blur the lines between moral judgments and science

1029
00:54:33,360 --> 00:54:36,960
Speaker 1: value judgments. Like you can study global warming, you can

1030
00:54:36,960 --> 00:54:40,520
Speaker 1: study cause and effect, you can report data, but when

1031
00:54:40,520 --> 00:54:44,520
Speaker 1: you make that secondly to say, and this is a scientist,

1032
00:54:44,600 --> 00:54:46,359
Speaker 1: I mean someone can come along and say global warming

1033
00:54:46,440 --> 00:54:49,279
Speaker 1: is bad, you shouldn't drive your suv. That's fine, But

1034
00:54:49,520 --> 00:54:52,960
Speaker 1: a scientist can't do a study and say that, because

1035
00:54:53,000 --> 00:54:58,440
Speaker 1: that's a value judgment. And that's where science can get corrupted.

1036
00:54:58,440 --> 00:55:01,920
Speaker 1: Pretty much. You can you can study glow warming and

1037
00:55:01,960 --> 00:55:05,680
Speaker 1: results till the cows come home, but you can't assert

1038
00:55:05,840 --> 00:55:09,040
Speaker 1: that if you use this light bulb you're a bad person.

1039
00:55:09,160 --> 00:55:13,439
Speaker 2: Right, or ocean and acidification is bad. It's not good

1040
00:55:13,440 --> 00:55:16,480
Speaker 2: for humans. But if you're a jellyfish is awesome, right

1041
00:55:16,560 --> 00:55:19,520
Speaker 2: you know? So yes, And again you made a great point.

1042
00:55:19,719 --> 00:55:24,600
Speaker 2: It's not science, it's people using science to make value judgments.

1043
00:55:24,680 --> 00:55:24,879
Speaker 1: Yeah.

1044
00:55:25,320 --> 00:55:29,040
Speaker 2: So it ultimately the scientific method, although it does have

1045
00:55:29,200 --> 00:55:33,919
Speaker 2: its limitations in that it needs empirical data to prove

1046
00:55:34,000 --> 00:55:38,600
Speaker 2: or disprove something. It's not. It's not flawed. That's not

1047
00:55:38,640 --> 00:55:42,279
Speaker 2: a flaw. That's a limitation, and it's it's when it's

1048
00:55:42,560 --> 00:55:47,160
Speaker 2: misused then it's results become flawed or skewed. And that's

1049
00:55:47,200 --> 00:55:49,080
Speaker 2: the people doing it, man, not science.

1050
00:55:49,239 --> 00:55:49,680
Speaker 1: That's right.

1051
00:55:49,760 --> 00:55:51,200
Speaker 2: It's pretty interesting stuff.

1052
00:55:51,320 --> 00:55:52,640
Speaker 1: Yeah, man, this is a good one.

1053
00:55:52,840 --> 00:55:53,560
Speaker 2: I thought so too.

1054
00:55:53,600 --> 00:55:56,600
Speaker 1: Man, let it start out with a bang boom. It's

1055
00:55:56,640 --> 00:55:57,839
Speaker 1: all downhill from here.

1056
00:55:59,040 --> 00:56:01,919
Speaker 2: If you want to know more about scientific method, check

1057
00:56:01,960 --> 00:56:06,000
Speaker 2: out that article on the Economists, check out explorables, and

1058
00:56:06,040 --> 00:56:08,560
Speaker 2: then of course, check out the scientific method in the

1059
00:56:08,560 --> 00:56:11,560
Speaker 2: search bar at HowStuffWorks dot com. And since I said that,

1060
00:56:11,680 --> 00:56:13,920
Speaker 2: it's time for listener mail.

1061
00:56:16,000 --> 00:56:20,520
Speaker 1: That's right. But quickly before listener mail, we get asked

1062
00:56:20,560 --> 00:56:23,399
Speaker 1: by listeners all the time, what can we do since

1063
00:56:23,400 --> 00:56:25,480
Speaker 1: you have a free podcast. We can't pay for it.

1064
00:56:25,800 --> 00:56:28,319
Speaker 1: What can we do to help you, guys? And one

1065
00:56:28,320 --> 00:56:32,000
Speaker 1: thing you can do that we would appreciate is go

1066
00:56:32,080 --> 00:56:34,920
Speaker 1: to iTunes and leave a rating in a review for us.

1067
00:56:35,400 --> 00:56:38,520
Speaker 1: That makes it big, big difference in keeping us up

1068
00:56:38,520 --> 00:56:41,360
Speaker 1: there in the rankings, which means more people find stuff

1069
00:56:41,360 --> 00:56:45,400
Speaker 1: you should know after they listen to Cereal, they'll just say, well, geez,

1070
00:56:45,400 --> 00:56:46,399
Speaker 1: there's other podcasts in.

1071
00:56:46,360 --> 00:56:49,239
Speaker 2: The world, what is this podcast?

1072
00:56:49,840 --> 00:56:52,400
Speaker 1: So ratings and reviews really help us out and it

1073
00:56:52,440 --> 00:56:55,440
Speaker 1: doesn't cost you anything but a few minutes. Be honest.

1074
00:56:55,440 --> 00:56:57,759
Speaker 1: We're not saying go leave us some great review, but

1075
00:56:58,040 --> 00:57:02,319
Speaker 1: go leave us a great review. You said it and

1076
00:57:02,400 --> 00:57:04,320
Speaker 1: told tell one person about stuff you should know. We

1077
00:57:04,360 --> 00:57:07,400
Speaker 1: would appreciate that too. Turn somebody onto the show, and

1078
00:57:08,640 --> 00:57:10,799
Speaker 1: that's it. That's our version of a pledge drive.

1079
00:57:11,640 --> 00:57:14,360
Speaker 2: They wow, we did that once every three years. No,

1080
00:57:14,800 --> 00:57:17,880
Speaker 2: not very obnoxious and it lasts forty seconds.

1081
00:57:18,000 --> 00:57:19,919
Speaker 1: All right, So on to listener mail. This is from

1082
00:57:19,920 --> 00:57:20,720
Speaker 1: my sister in law.

1083
00:57:20,760 --> 00:57:23,240
Speaker 2: Actually, oh yeah, there's some nepotism.

1084
00:57:23,400 --> 00:57:28,360
Speaker 1: Yeah, Jenny. Jenny Bryant, she mentioned in the homeschool episode

1085
00:57:28,360 --> 00:57:31,960
Speaker 1: homeschooled her kids for a little while and she sort

1086
00:57:31,960 --> 00:57:35,560
Speaker 1: of corrected me. Loved the homeschooling episode. Guys. One very

1087
00:57:35,560 --> 00:57:40,640
Speaker 1: big trend these days in the homeschooling community is what Abby,

1088
00:57:40,760 --> 00:57:44,640
Speaker 1: my niece does, which is hybrid homeschooling. So two to

1089
00:57:44,680 --> 00:57:47,520
Speaker 1: three days a week she is at school and then

1090
00:57:47,680 --> 00:57:50,320
Speaker 1: the rest of the time she is a plant. She's

1091
00:57:50,320 --> 00:57:52,920
Speaker 1: not a plant. The rest of the time she's a

1092
00:57:52,960 --> 00:57:55,280
Speaker 1: home So she says it's a great option with curriculum

1093
00:57:55,320 --> 00:57:58,480
Speaker 1: provided and new topics ought at school and then worked

1094
00:57:58,520 --> 00:58:01,960
Speaker 1: out at home. Any of these schools are accredited making

1095
00:58:02,040 --> 00:58:06,160
Speaker 1: getting into college, including Ivy League schools, hassel Free and

1096
00:58:06,400 --> 00:58:10,280
Speaker 1: Abby School has sports teams, homecoming. Abby's actually an excellent

1097
00:58:10,360 --> 00:58:14,560
Speaker 1: volleyball player. Yeah, Beta club, newspaper staff, all the good stuff.

1098
00:58:15,120 --> 00:58:17,600
Speaker 1: The flexibility is great for families, and we are huge

1099
00:58:17,600 --> 00:58:20,760
Speaker 1: fans of how the hybrid approach prepares students for college

1100
00:58:21,000 --> 00:58:23,440
Speaker 1: by allowing them time outside of class to manage their

1101
00:58:23,480 --> 00:58:24,640
Speaker 1: work and life schedules.

1102
00:58:25,360 --> 00:58:30,000
Speaker 2: So that's from Jenny Nice. It's actually Jenny via text over.

1103
00:58:30,000 --> 00:58:31,800
Speaker 1: The first listener mail via text.

1104
00:58:31,800 --> 00:58:34,320
Speaker 2: How did you print that out? Did you retype it

1105
00:58:34,360 --> 00:58:38,200
Speaker 2: and print it? Oh dude, are you serious? You can

1106
00:58:38,240 --> 00:58:39,120
Speaker 2: print from texts?

1107
00:58:39,240 --> 00:58:42,000
Speaker 1: No, you just copy pasted to an email.

1108
00:58:42,040 --> 00:58:44,800
Speaker 2: Oh oh yeah, yeah, I forgot about that method. How

1109
00:58:44,880 --> 00:58:48,600
Speaker 2: in the world did you do that with your thoughts?

1110
00:58:49,240 --> 00:58:52,120
Speaker 2: I have a niece who is excellent at volleyball too.

1111
00:58:52,200 --> 00:58:52,840
Speaker 2: Oh yeah, how old?

1112
00:58:52,880 --> 00:58:55,360
Speaker 1: We should get them together, James, I don't know ten

1113
00:58:55,400 --> 00:58:58,200
Speaker 1: to eleven, Okay, something like that. Abby just turned thirteen,

1114
00:58:58,280 --> 00:58:59,040
Speaker 1: so they're.

1115
00:58:59,000 --> 00:59:00,920
Speaker 2: Oh, maybe they face all up against one another.

1116
00:59:01,000 --> 00:59:02,120
Speaker 1: Yeah. Is she in Atlanta?

1117
00:59:02,760 --> 00:59:06,120
Speaker 2: Yes, she's up in Canton. You never know where's Abby.

1118
00:59:06,560 --> 00:59:09,000
Speaker 1: She's in Roswell. But they I think with volleyball they

1119
00:59:09,080 --> 00:59:10,960
Speaker 1: kind of have played all over the state.

1120
00:59:11,040 --> 00:59:12,520
Speaker 2: It'd be bizarre if they play each other.

1121
00:59:12,640 --> 00:59:14,560
Speaker 1: Yeah, we'll just see each other at a match one day,

1122
00:59:15,040 --> 00:59:17,320
Speaker 1: on opposite sides of the court with our arms folded.

1123
00:59:17,440 --> 00:59:19,840
Speaker 2: Yeah, what else?

1124
00:59:20,320 --> 00:59:21,200
Speaker 1: I got nothing else?

1125
00:59:21,360 --> 00:59:24,560
Speaker 2: Well, like Chuck said, go leave us a review. And

1126
00:59:24,800 --> 00:59:26,320
Speaker 2: if you want to get in touch with us, you

1127
00:59:26,360 --> 00:59:29,640
Speaker 2: can tweet to us at sysk podcast. You can join

1128
00:59:29,760 --> 00:59:32,360
Speaker 2: us on Facebook, dot com, slash Stuff you Should Know.

1129
00:59:32,880 --> 00:59:37,000
Speaker 2: You can email us, We still do that. Yeah, you

1130
00:59:37,040 --> 00:59:41,400
Speaker 2: can't text me and stuff podcast at HowStuffWorks dot com

1131
00:59:41,440 --> 00:59:43,479
Speaker 2: and has always joined us at our home on the web,

1132
00:59:43,640 --> 00:59:50,920
Speaker 2: Stuff you Should Know dot com For more on this,

1133
00:59:51,000 --> 01:00:01,280
Speaker 2: and thousands of other topics. Visit HowStuffWorks dot com.