1 00:00:00,160 --> 00:00:04,440 Speaker 1: Yeah, welcome to Stuff from the Science Lab from how 2 00:00:04,480 --> 00:00:16,160 Speaker 1: stuff works dot com. Hey guys, and welcome to the podcast. 3 00:00:16,200 --> 00:00:17,959 Speaker 1: This is Alison I don't know if, the science editor 4 00:00:18,079 --> 00:00:20,759 Speaker 1: at how staff works dot com. And this is Robert Lamb, 5 00:00:20,760 --> 00:00:22,680 Speaker 1: science writerer at how stuff works dot com. And this 6 00:00:22,760 --> 00:00:27,480 Speaker 1: is part two of a two parter. Last episode, um 7 00:00:27,680 --> 00:00:30,800 Speaker 1: thing called science. We talked about what science is in 8 00:00:30,920 --> 00:00:34,440 Speaker 1: very sort of broad general terms, um, you know, defining 9 00:00:35,000 --> 00:00:37,400 Speaker 1: this thing called science and what it, what it means, 10 00:00:37,400 --> 00:00:41,040 Speaker 1: how it works, and uh, and how it's changed what 11 00:00:41,320 --> 00:00:44,400 Speaker 1: we are as a species and civilization. Yeah, we've gotten 12 00:00:44,400 --> 00:00:46,680 Speaker 1: a couple of requests for doing a podcast on the 13 00:00:46,720 --> 00:00:48,960 Speaker 1: scientific method, and we will be tackling some of these 14 00:00:48,960 --> 00:00:51,839 Speaker 1: big topics. And it really was important to us to 15 00:00:51,880 --> 00:00:54,520 Speaker 1: talk about the scientific method, as it is a core 16 00:00:54,600 --> 00:00:58,560 Speaker 1: concept of all science. Yeah, like scientific method as um, 17 00:00:58,600 --> 00:01:02,840 Speaker 1: as we mentioned the Life podcast, it's basically how science advances, 18 00:01:02,840 --> 00:01:05,880 Speaker 1: how it moves, how it claims new territory like a 19 00:01:06,360 --> 00:01:09,560 Speaker 1: like an advancing army. You know, how it you know 20 00:01:09,600 --> 00:01:11,600 Speaker 1: how it's a quote you know, Carl Sagan, how it 21 00:01:11,920 --> 00:01:16,679 Speaker 1: you know, brings light into a demon haunted world. You know. So, 22 00:01:16,680 --> 00:01:18,920 Speaker 1: so what's the history on scientific method. Right when did 23 00:01:18,959 --> 00:01:21,720 Speaker 1: it come out? Come about? It looks like it came 24 00:01:21,760 --> 00:01:25,399 Speaker 1: out as far back as the fourth century. See though 25 00:01:25,440 --> 00:01:28,280 Speaker 1: they didn't call it scientific method, and it's it can't 26 00:01:28,280 --> 00:01:31,480 Speaker 1: really be attributed to like one person, but but some 27 00:01:31,560 --> 00:01:33,920 Speaker 1: of the like the ideas involved, and it started emerging 28 00:01:33,959 --> 00:01:36,640 Speaker 1: pretty early on. Yeah, you got a guy you guys 29 00:01:36,720 --> 00:01:39,920 Speaker 1: might have heard of him in Aristotle. He proposed methods 30 00:01:39,959 --> 00:01:43,160 Speaker 1: to answer questions about the world through rigorous observation. Yeah, 31 00:01:43,280 --> 00:01:46,679 Speaker 1: that was way back in the fourth century BC. Much later, 32 00:01:47,280 --> 00:01:51,520 Speaker 1: Albertus Magnus comes along and he borrowed some principles from 33 00:01:51,600 --> 00:01:56,880 Speaker 1: Muslim scientists, and he described this repeating cycle of observation, hypothesis, experimentation, 34 00:01:56,960 --> 00:02:00,120 Speaker 1: and verification. Do you know that Albertus Magnus suppose as 35 00:02:00,120 --> 00:02:04,120 Speaker 1: we had an android? I'm sorry what and android? Yeah, 36 00:02:04,320 --> 00:02:06,920 Speaker 1: it's like look it up. It's pretty crazy, like it 37 00:02:07,000 --> 00:02:09,240 Speaker 1: was probably not an actual robot, just to go ahead 38 00:02:09,240 --> 00:02:11,520 Speaker 1: and get that out there. But um, but he had 39 00:02:11,560 --> 00:02:13,480 Speaker 1: like some sort if I remember the scry he hit 40 00:02:13,560 --> 00:02:16,680 Speaker 1: some sort of like mannequin that maybe had some sort 41 00:02:16,680 --> 00:02:21,560 Speaker 1: of mechanical I think those those charges may have been 42 00:02:21,600 --> 00:02:23,760 Speaker 1: because a lot of these older guys like our next guy, 43 00:02:23,760 --> 00:02:27,080 Speaker 1: Francis Bacon included. You know, they were curious about a 44 00:02:27,080 --> 00:02:29,440 Speaker 1: lot of things, and sometimes that curiosity took them into, 45 00:02:29,680 --> 00:02:35,200 Speaker 1: you know, exploring um less scientific and more magical ideas, 46 00:02:35,240 --> 00:02:37,280 Speaker 1: you know, because that was, like I said, you didn't 47 00:02:37,280 --> 00:02:39,520 Speaker 1: have as clearly to find a science back then, so 48 00:02:39,600 --> 00:02:44,080 Speaker 1: it would sort of bleed into other areas. Um. But 49 00:02:44,080 --> 00:02:46,839 Speaker 1: but yeah, he supposedly had an android, Francis Bacon. I don't. 50 00:02:46,960 --> 00:02:49,239 Speaker 1: I don't think he did. But and he's important we 51 00:02:49,280 --> 00:02:51,000 Speaker 1: bring him up because he was really the first to 52 00:02:51,040 --> 00:02:54,400 Speaker 1: formalize the concept of a true scientific method. And he, 53 00:02:54,600 --> 00:02:57,200 Speaker 1: of course, as standing on the shoulders of giants, as 54 00:02:57,200 --> 00:03:00,920 Speaker 1: these scientists tend to you, was basing is method on 55 00:03:01,120 --> 00:03:06,120 Speaker 1: the work of Nicolas Caperncus and Galileo. Yeah, then along 56 00:03:06,200 --> 00:03:10,880 Speaker 1: comes Mr Newton, Sir Newton to us and his laws 57 00:03:10,919 --> 00:03:13,680 Speaker 1: really ruled the world of science for centuries, and he 58 00:03:13,720 --> 00:03:17,000 Speaker 1: marked the beaming of the scientific age. And don't we 59 00:03:17,040 --> 00:03:18,680 Speaker 1: have a we have a really good article on Isaac 60 00:03:18,720 --> 00:03:20,400 Speaker 1: Newton on the side, don't we do? And I have 61 00:03:20,440 --> 00:03:24,239 Speaker 1: an outstanding request to do a blog post on oh yes, 62 00:03:24,280 --> 00:03:29,519 Speaker 1: about his um, his involvement in alchemy and I remember else. 63 00:03:29,760 --> 00:03:33,400 Speaker 1: I know it's arianism, Okay, Newton and arianism, So I 64 00:03:33,440 --> 00:03:36,200 Speaker 1: will get to that at some point, I promise. Cool. 65 00:03:36,520 --> 00:03:39,840 Speaker 1: So yeah, Newton, though, was pretty much the the beginning 66 00:03:39,840 --> 00:03:44,920 Speaker 1: of the the you know, our scientific age. And you 67 00:03:44,960 --> 00:03:48,480 Speaker 1: know he brought about the beginning methods to um an 68 00:03:48,480 --> 00:03:51,320 Speaker 1: attempt to minimize the influence of bias and prejudice in 69 00:03:51,360 --> 00:03:55,400 Speaker 1: the experiment or and and and the scientific method also 70 00:03:56,520 --> 00:04:01,880 Speaker 1: provides an objective, standardized approach to conducting experiments. And it's 71 00:04:01,880 --> 00:04:04,360 Speaker 1: also about getting cred right, you know, it's good, but 72 00:04:04,360 --> 00:04:06,280 Speaker 1: it's about getting cred not only with other scientists, but 73 00:04:06,360 --> 00:04:08,560 Speaker 1: with the public, with you know, the people who are 74 00:04:08,560 --> 00:04:11,720 Speaker 1: going to be um, exposed to your work. And how 75 00:04:11,720 --> 00:04:14,440 Speaker 1: do they know, um, that you're conducting your work in 76 00:04:14,480 --> 00:04:18,400 Speaker 1: a controlled and rigorous fashion. Yeah, and you made a 77 00:04:18,400 --> 00:04:22,240 Speaker 1: good point when we were preparing for this about nobody's 78 00:04:22,279 --> 00:04:25,600 Speaker 1: perfect when it comes to experimentation in carrying out the 79 00:04:25,640 --> 00:04:28,480 Speaker 1: scientific method, Like there's no like we've named some pretty 80 00:04:28,560 --> 00:04:31,159 Speaker 1: you know, stellar names, you know, um, you know, be 81 00:04:31,240 --> 00:04:35,080 Speaker 1: at Aristotle or Galileo or Newton, but nobody's like free 82 00:04:35,080 --> 00:04:38,479 Speaker 1: of criticism, you know, even like modern dudes like like hawking. 83 00:04:38,839 --> 00:04:42,159 Speaker 1: You know, it's like people. People will and do take 84 00:04:42,200 --> 00:04:44,480 Speaker 1: hawking to task the things that they think doesn't hold 85 00:04:44,560 --> 00:04:48,279 Speaker 1: up to scientific scrutiny. And that's that's how science works. 86 00:04:48,320 --> 00:04:51,240 Speaker 1: Like nothing is set in stone, right, So you have 87 00:04:51,320 --> 00:04:55,400 Speaker 1: to be open to colleagues, um, feedback, constructive criticism, although 88 00:04:55,440 --> 00:04:58,000 Speaker 1: sometimes it can get a little gnarly. Uh. You know, 89 00:04:58,040 --> 00:05:00,320 Speaker 1: you can have some like the bone war. Do you 90 00:05:00,320 --> 00:05:05,320 Speaker 1: remember that when we're talking about dinosaurs. These respected scholars, paleontologists, 91 00:05:05,720 --> 00:05:08,240 Speaker 1: and all of a sudden they're battling over dinosaur bones. 92 00:05:08,279 --> 00:05:11,200 Speaker 1: And I published first. Now you published first, and never 93 00:05:11,279 --> 00:05:13,400 Speaker 1: having been in in a career where I need to 94 00:05:13,400 --> 00:05:15,480 Speaker 1: publish to get ahead, I imagine it does get very 95 00:05:15,520 --> 00:05:18,279 Speaker 1: heated and the pressure is on to publish, to get funding, 96 00:05:18,320 --> 00:05:20,480 Speaker 1: all the stuff, to be the one who's in Nature 97 00:05:20,560 --> 00:05:25,360 Speaker 1: first or whatever publication. But getting back to your point, 98 00:05:26,480 --> 00:05:29,920 Speaker 1: Highlights was a good managing. They had the page where 99 00:05:29,920 --> 00:05:32,720 Speaker 1: you would find the hidden objects in the I did. 100 00:05:32,800 --> 00:05:35,240 Speaker 1: I used to read that in the doctor's office. Um. 101 00:05:35,320 --> 00:05:37,880 Speaker 1: You know, beginning back to your point, there are two 102 00:05:38,520 --> 00:05:41,440 Speaker 1: major forms of bias that creep into experiments and we 103 00:05:41,480 --> 00:05:45,599 Speaker 1: should mention them. Uh, selection bias and that's really that 104 00:05:45,640 --> 00:05:49,359 Speaker 1: occurs if the participants you select, for example, UM for 105 00:05:49,400 --> 00:05:53,800 Speaker 1: an experiment aren't representative of particular population, so selection bias. 106 00:05:53,920 --> 00:05:59,720 Speaker 1: Say you're interested in whether people watch more TV at night, 107 00:06:00,360 --> 00:06:04,280 Speaker 1: but you only go to a house. Uh, you only 108 00:06:04,279 --> 00:06:07,320 Speaker 1: go to a neighborhood that's fifty five and older. So yeah, 109 00:06:07,320 --> 00:06:10,480 Speaker 1: that's not a good like cross section of the population 110 00:06:10,560 --> 00:06:13,840 Speaker 1: you're looking to to study. Yeah, because maybe you're looking 111 00:06:13,880 --> 00:06:18,240 Speaker 1: to look at TV habit TV watching habits in population 112 00:06:18,400 --> 00:06:21,480 Speaker 1: from thirty and above, right, So you're if you're only 113 00:06:21,520 --> 00:06:23,640 Speaker 1: hitting the fifty five and older community, probably not going 114 00:06:23,680 --> 00:06:26,360 Speaker 1: to get that creative results. I'm not going to have 115 00:06:26,400 --> 00:06:30,200 Speaker 1: an informed, informed data. So you also can have observer bias. 116 00:06:30,240 --> 00:06:32,719 Speaker 1: An example of this may be that a participant in 117 00:06:32,760 --> 00:06:37,120 Speaker 1: experiment couldn't remember correctly what his exposure to particular variable was. 118 00:06:37,680 --> 00:06:42,159 Speaker 1: So let's say you're interested in the question of UM 119 00:06:42,279 --> 00:06:48,159 Speaker 1: influenza among UM a particular population of people, and UM, 120 00:06:48,600 --> 00:06:51,320 Speaker 1: your participant can't remember the number of times he hung 121 00:06:51,320 --> 00:06:54,479 Speaker 1: out with runny nose nursery school kids. However, you choose 122 00:06:54,480 --> 00:06:57,240 Speaker 1: to word that in your experiment, Well cool, let's UM. 123 00:06:57,279 --> 00:07:00,080 Speaker 1: So those are two examples of us cool. Well, let's so, 124 00:07:00,279 --> 00:07:03,240 Speaker 1: I guess it's time to actually begin the process, begin 125 00:07:03,600 --> 00:07:07,000 Speaker 1: the scientific method. Let's do it right. So the first 126 00:07:07,040 --> 00:07:10,680 Speaker 1: step is pretty pretty basic, doesn't require a lot of explanation. 127 00:07:11,040 --> 00:07:14,000 Speaker 1: Make an observation, and you know, I think, well, you 128 00:07:14,080 --> 00:07:15,920 Speaker 1: encounter this every day. You like, maybe you're on Marty 129 00:07:16,040 --> 00:07:18,920 Speaker 1: or something that Marty's our public transportation train system here 130 00:07:18,960 --> 00:07:21,240 Speaker 1: in Atlanta, and you you look across the island and 131 00:07:21,240 --> 00:07:24,320 Speaker 1: you go, I wonder, like, what why that lady is 132 00:07:24,320 --> 00:07:27,880 Speaker 1: eating an entyrotistrie chicken on the train. It's an observation 133 00:07:28,040 --> 00:07:31,280 Speaker 1: and it raises question, chicken lady, it was weird, it 134 00:07:31,400 --> 00:07:34,920 Speaker 1: was It's kind of gross. That would be definitely gross. Yeah, 135 00:07:35,120 --> 00:07:38,000 Speaker 1: now that would would be harder to that more scientific 136 00:07:38,040 --> 00:07:41,920 Speaker 1: would be like you know, like Charles Darwin observing uh, 137 00:07:42,200 --> 00:07:45,520 Speaker 1: you know, different species of finches uh on the galactical 138 00:07:45,600 --> 00:07:49,360 Speaker 1: silence and and asking himself, you know, what's going on here? Why? 139 00:07:49,600 --> 00:07:52,280 Speaker 1: Why all the similarity? You know, or you know, the 140 00:07:52,360 --> 00:07:54,840 Speaker 1: things of that nature are definitely more in the scientific realm. 141 00:07:54,920 --> 00:07:57,960 Speaker 1: Why is something the way it is? And And that's 142 00:07:58,040 --> 00:08:01,440 Speaker 1: that's the beginning. Okay, But let's just get back to 143 00:08:01,480 --> 00:08:05,600 Speaker 1: the richistory. Chicken. There's no reason why you couldn't um 144 00:08:05,760 --> 00:08:08,920 Speaker 1: come up with some sort of interesting experiment based around that. Okay, 145 00:08:08,920 --> 00:08:11,480 Speaker 1: well okay, yeah, Like the in the situation would be 146 00:08:11,520 --> 00:08:15,760 Speaker 1: like why does this lady find it necessary to eat 147 00:08:15,760 --> 00:08:18,440 Speaker 1: a roctistory chicken with their fingers on the train and 148 00:08:18,440 --> 00:08:23,000 Speaker 1: then touch the pole? There's there's all sorts of interesting 149 00:08:23,040 --> 00:08:25,320 Speaker 1: stuff to be explored there. It doesn't have to be 150 00:08:25,360 --> 00:08:29,440 Speaker 1: about finches or about you know, particle accelerators. The very 151 00:08:29,520 --> 00:08:32,160 Speaker 1: questions that you know surround us in our normal lives, 152 00:08:32,160 --> 00:08:34,560 Speaker 1: I think are worthy of investigation, and I think it's 153 00:08:34,559 --> 00:08:37,880 Speaker 1: just really worth emphasizing because science does not have to 154 00:08:37,920 --> 00:08:42,199 Speaker 1: be about these um super unapproachable intellectual topics, right like 155 00:08:43,000 --> 00:08:48,640 Speaker 1: the the Ignoble Prizes, the Improbable Research publication they constantly 156 00:08:48,640 --> 00:08:52,400 Speaker 1: cover peer reviewed scientific um, you know, papers that deal 157 00:08:52,440 --> 00:08:55,840 Speaker 1: with kind of ludicrous founding, you know, questions, But but 158 00:08:55,920 --> 00:08:58,080 Speaker 1: nothing's you know, like you say, nothing is really out 159 00:08:58,080 --> 00:09:01,120 Speaker 1: of bounds for science, you knows, of like, what was 160 00:09:01,160 --> 00:09:03,040 Speaker 1: one of the more ridiculous ones that I can actually 161 00:09:03,120 --> 00:09:05,720 Speaker 1: mention in the podcast because the only ones coming to 162 00:09:05,760 --> 00:09:09,640 Speaker 1: mind are the probably risque ones. Um, I think there 163 00:09:09,720 --> 00:09:13,240 Speaker 1: was something that's um, there was a charcoal filter. A 164 00:09:13,320 --> 00:09:17,080 Speaker 1: man who invented a charcoal filter so that when he 165 00:09:17,280 --> 00:09:24,280 Speaker 1: um was feeling gaseous, there was That wasn't really an experiment, 166 00:09:24,280 --> 00:09:27,480 Speaker 1: that was more of an invention, I suppose. Yeah, but 167 00:09:27,800 --> 00:09:29,520 Speaker 1: that's the only one I can do. But still the 168 00:09:29,600 --> 00:09:32,040 Speaker 1: things of that nature. I mean, there are some scientific 169 00:09:32,080 --> 00:09:34,920 Speaker 1: experiments I know for a fact, like dealing with NASA 170 00:09:35,040 --> 00:09:37,000 Speaker 1: that have to do with like how ghassy people are, 171 00:09:37,040 --> 00:09:40,000 Speaker 1: because that's an issue if you're going into space, so 172 00:09:40,240 --> 00:09:44,080 Speaker 1: bad breath. So yeah, just about anything, no matter how 173 00:09:44,160 --> 00:09:49,840 Speaker 1: ridiculous or seemingly insignificant. Uh, science can and often does 174 00:09:50,000 --> 00:09:54,440 Speaker 1: analyze it. So we have a pretty insignificant sounding example, 175 00:09:54,559 --> 00:09:57,240 Speaker 1: just a very hypothetical situation here around the office, right 176 00:09:57,480 --> 00:09:59,400 Speaker 1: all right, Yeah, So Robert and I put together a 177 00:09:59,440 --> 00:10:03,440 Speaker 1: little hype local experiment and here's our experiment. We were 178 00:10:03,440 --> 00:10:07,800 Speaker 1: going to make an observation. And here's the deal. Robert, Yeah, 179 00:10:08,120 --> 00:10:11,920 Speaker 1: you are a big fan of pudding pops and for 180 00:10:11,960 --> 00:10:15,800 Speaker 1: the purposes, so you're gonna be bringing a stash of 181 00:10:15,840 --> 00:10:18,840 Speaker 1: putting pops to work. You're gonna put them in the freezer, 182 00:10:19,520 --> 00:10:21,360 Speaker 1: don't put them in the fridge like I put my 183 00:10:21,400 --> 00:10:23,880 Speaker 1: ice cream cake for my sixteenth birthday in the fridge 184 00:10:23,880 --> 00:10:25,959 Speaker 1: and it melted, and that was why do you bring 185 00:10:26,000 --> 00:10:29,120 Speaker 1: that to work? Now? It probably just as well you 186 00:10:29,160 --> 00:10:34,200 Speaker 1: shouldn't eat baconized turning sixty. Um, So, anyway, you've been 187 00:10:34,200 --> 00:10:36,600 Speaker 1: bringing these pudding pops to work. He's stash him in 188 00:10:36,600 --> 00:10:38,920 Speaker 1: the freezer. Two clock rolls around. You're really getting that, 189 00:10:39,920 --> 00:10:41,920 Speaker 1: you know, urge for a pudding pop, which I guess 190 00:10:42,240 --> 00:10:45,560 Speaker 1: grips some of us. Yeah, two pm, that's a good 191 00:10:45,600 --> 00:10:48,560 Speaker 1: time for it. Sugar, you need some sugar to keep going. Yeah, 192 00:10:48,559 --> 00:10:50,720 Speaker 1: so you even noticing that the pudding pops are disappearing. 193 00:10:51,240 --> 00:10:54,720 Speaker 1: Mm hmm. They're disappearing faster than you've been eating them. 194 00:10:54,760 --> 00:10:59,080 Speaker 1: At least this is your thought. It's not like you're 195 00:10:59,120 --> 00:11:01,400 Speaker 1: the kind of guy who you know, marks his food 196 00:11:01,400 --> 00:11:03,880 Speaker 1: and the freezer and ticks one off when you take 197 00:11:03,920 --> 00:11:06,720 Speaker 1: one out of the box. So you've you've kind of observed. Okay, 198 00:11:06,760 --> 00:11:10,920 Speaker 1: we've observed. And this leads right into the next step 199 00:11:11,080 --> 00:11:14,200 Speaker 1: in the scientific method, and that is ask a question. Yeah, 200 00:11:14,280 --> 00:11:17,000 Speaker 1: we gotta narrow our focus of inquiry. We've gotta identify 201 00:11:17,080 --> 00:11:20,079 Speaker 1: the problem. We're gonna get specific, right, So the observation 202 00:11:20,120 --> 00:11:23,560 Speaker 1: we made was that something is happening to these pudding pops. 203 00:11:23,640 --> 00:11:25,800 Speaker 1: They're vanishing. Am I the only one thinking of Bill 204 00:11:25,840 --> 00:11:31,640 Speaker 1: Cosby right now? Probably not um? And then the question 205 00:11:31,679 --> 00:11:35,680 Speaker 1: that immediately arises is, Hey, what's happening to these pudding pops? 206 00:11:36,000 --> 00:11:38,880 Speaker 1: Is someone throwing them away? Are they like they are 207 00:11:38,880 --> 00:11:41,880 Speaker 1: they atomizing and just you know, or they've slipping into 208 00:11:41,920 --> 00:11:45,320 Speaker 1: another dimension. And maybe the boxes upside down and they're 209 00:11:45,480 --> 00:11:47,640 Speaker 1: they're falling out of the boxing on the way to work, 210 00:11:47,679 --> 00:11:50,640 Speaker 1: and then I'm putting an empty box into the freezer. See, 211 00:11:50,679 --> 00:11:53,559 Speaker 1: these are all these are all interesting possible Maybe just 212 00:11:53,640 --> 00:11:57,800 Speaker 1: maybe somebody is eating your pudding pops and it's not you. 213 00:11:58,040 --> 00:12:01,480 Speaker 1: Well that leads to step three right, form a hypothesis. 214 00:12:02,520 --> 00:12:05,319 Speaker 1: So there are all these possibilities. Now that the possibility 215 00:12:05,320 --> 00:12:07,600 Speaker 1: that a a like a tiny black hole is opening 216 00:12:07,679 --> 00:12:10,960 Speaker 1: up in the house, stuff works, freezer and consuming pudding pops, well, 217 00:12:11,120 --> 00:12:14,520 Speaker 1: I don't think that's very likely. Just it's maybe it's possible, 218 00:12:14,520 --> 00:12:18,600 Speaker 1: but it's extremely unlikely. Likewise, I feel like I'm pretty 219 00:12:19,040 --> 00:12:21,680 Speaker 1: aware of my you know, surroundings. When I'm bringing things 220 00:12:21,679 --> 00:12:24,079 Speaker 1: to work. They're probably not following out falling out of 221 00:12:24,120 --> 00:12:27,120 Speaker 1: that box. So I'm going to go with the hypothesis 222 00:12:27,880 --> 00:12:33,319 Speaker 1: somebody's stealing my pudding pops. Well, if they're vanilla flavor, 223 00:12:33,400 --> 00:12:36,080 Speaker 1: nobody's stealing them chocolate, I might grant you that. So 224 00:12:36,679 --> 00:12:39,200 Speaker 1: um right, So no, now we have this question, and 225 00:12:39,280 --> 00:12:41,680 Speaker 1: let's let's formulate it correctly so that we can find 226 00:12:41,679 --> 00:12:44,360 Speaker 1: an answer. And that's really the next step that we 227 00:12:44,440 --> 00:12:46,280 Speaker 1: have going on here. We're going to suggest a possible 228 00:12:46,280 --> 00:12:50,240 Speaker 1: answer in the form of a hypothesis. And a hypothesis 229 00:12:50,360 --> 00:12:54,280 Speaker 1: is often defined as an educated guess because we sort 230 00:12:54,280 --> 00:12:57,080 Speaker 1: of have this idea that, yes, maybe somebody is taking 231 00:12:57,080 --> 00:13:00,439 Speaker 1: the pudding pops black holes not really not really likely. 232 00:13:00,600 --> 00:13:02,640 Speaker 1: Some of the other options not so likely, So this 233 00:13:02,720 --> 00:13:06,120 Speaker 1: is somewhat of an informed guess. It's generally in the 234 00:13:06,160 --> 00:13:09,880 Speaker 1: form of like X then y R. Another important thing 235 00:13:09,880 --> 00:13:11,960 Speaker 1: about the hypothesis is that you're gonna have to define 236 00:13:12,040 --> 00:13:14,880 Speaker 1: all the terms in there, right, So um, if our 237 00:13:14,960 --> 00:13:21,480 Speaker 1: hypothesis is um, let's see if we leave a box 238 00:13:21,559 --> 00:13:24,320 Speaker 1: putting pops in the fridge for a week, then Josh 239 00:13:24,440 --> 00:13:26,839 Speaker 1: Clark from Stuff you Should Know, We'll still a pudding 240 00:13:26,880 --> 00:13:29,960 Speaker 1: pop a day in the afternoon. Accepting weekends, Okay, So 241 00:13:30,000 --> 00:13:31,480 Speaker 1: what are we gonna have to define there? Who is 242 00:13:31,559 --> 00:13:37,400 Speaker 1: Josh Clark? What is it? Pudding pop um? What is stealing? Indeed, 243 00:13:37,760 --> 00:13:39,520 Speaker 1: a couple of different things that we're going to have 244 00:13:39,600 --> 00:13:42,160 Speaker 1: to know and be able to measure to see in 245 00:13:42,200 --> 00:13:46,320 Speaker 1: fact whether our hypothesis has proven true. And how are 246 00:13:46,320 --> 00:13:48,600 Speaker 1: we going to find out if it's proven true. We're 247 00:13:48,600 --> 00:13:51,160 Speaker 1: gonna have to devise an experiment. Okay, and this is 248 00:13:51,200 --> 00:13:55,040 Speaker 1: step four, Step four duct an experiment the excitement. So 249 00:13:55,080 --> 00:13:58,440 Speaker 1: the hypothesis is that Josh Clark may be stealing these 250 00:13:58,559 --> 00:14:01,480 Speaker 1: putting pop a day and said, just to clarify, I'm 251 00:14:01,480 --> 00:14:04,560 Speaker 1: pretty sure Josh Clark is a fan of frozen yogurt 252 00:14:04,640 --> 00:14:06,680 Speaker 1: and not putting pops but in real life, but for 253 00:14:06,720 --> 00:14:10,520 Speaker 1: the purposes the experiment, he's a putting pop faint. Okay, 254 00:14:10,559 --> 00:14:14,839 Speaker 1: all right, so let's connect our experiment. Let's make it scientific. 255 00:14:15,040 --> 00:14:17,480 Speaker 1: All right? Well, how do you can connect the scientific experiment? Like? 256 00:14:17,520 --> 00:14:20,360 Speaker 1: What are the well, I mean a lot of people listening. 257 00:14:20,360 --> 00:14:21,760 Speaker 1: You are going to think of something that takes place 258 00:14:21,760 --> 00:14:23,600 Speaker 1: in the lab. You know you're gonna invoke buns and 259 00:14:23,640 --> 00:14:27,480 Speaker 1: burners and lab work benches and test tubes and all 260 00:14:27,520 --> 00:14:31,000 Speaker 1: sorts of things like that earln Meyer, Flaska. Do you 261 00:14:31,000 --> 00:14:35,360 Speaker 1: remember this? Yeah, I think so. But it doesn't necessarily 262 00:14:35,440 --> 00:14:37,880 Speaker 1: mean like, it doesn't necessarily mean like me and Alison 263 00:14:37,880 --> 00:14:40,520 Speaker 1: going into the laboratory and like melting down putting pops 264 00:14:40,560 --> 00:14:43,320 Speaker 1: and like you know that kind of stuff. No, our 265 00:14:43,320 --> 00:14:45,880 Speaker 1: experiment can be pretty simple, and and some really great 266 00:14:45,920 --> 00:14:49,720 Speaker 1: experiments in science have been extraordinarily simple. Yeah, it's all 267 00:14:49,760 --> 00:14:52,080 Speaker 1: about like not that we would put our experiment on 268 00:14:52,160 --> 00:14:54,960 Speaker 1: the level of this, but it's all about like keeping 269 00:14:54,960 --> 00:14:58,080 Speaker 1: it on task and in avoiding bias, so like in 270 00:14:58,200 --> 00:15:01,480 Speaker 1: controlling for your variables as much as you can um 271 00:15:01,520 --> 00:15:03,280 Speaker 1: and then you know, if you can't control for some 272 00:15:03,360 --> 00:15:07,440 Speaker 1: of these variables and analyzing the data uh later in 273 00:15:07,480 --> 00:15:10,480 Speaker 1: a way that can say maybe you run like linear regression. 274 00:15:10,520 --> 00:15:14,440 Speaker 1: I can't believe I just pull that up stats. Yeah, 275 00:15:14,520 --> 00:15:17,440 Speaker 1: So you wouldn't want to, like, you're not conducting an 276 00:15:17,440 --> 00:15:21,120 Speaker 1: experiment to prove Josh Clark is is stealing putting pops. 277 00:15:21,120 --> 00:15:24,560 Speaker 1: You're testing a hypothesis. It's it's it may seem like 278 00:15:24,560 --> 00:15:26,920 Speaker 1: a slight thing, but it's it really makes a lot 279 00:15:27,000 --> 00:15:30,480 Speaker 1: of difference. You're you're you're supposed to avoid having any 280 00:15:30,520 --> 00:15:33,960 Speaker 1: kind of like preconceived answer, you know. I mean you 281 00:15:33,960 --> 00:15:35,480 Speaker 1: can have you can sort of have one, but not 282 00:15:35,520 --> 00:15:39,920 Speaker 1: like officially. You know, you can have an informed guess. Yeah, 283 00:15:40,000 --> 00:15:42,680 Speaker 1: you can have expected result, but not you know, you're 284 00:15:42,680 --> 00:15:46,760 Speaker 1: not setting out to prove that result exactly. Okay, so 285 00:15:46,920 --> 00:15:49,080 Speaker 1: let's uh, let's roll our experiment. What are we gonna do. 286 00:15:49,320 --> 00:15:53,000 Speaker 1: We gotta get some pops, right, Um, So let's say 287 00:15:53,040 --> 00:15:55,760 Speaker 1: we were going to conduct our experiment over the span 288 00:15:55,960 --> 00:16:00,200 Speaker 1: of a work week Monday through Friday. We're gonna put 289 00:16:00,200 --> 00:16:03,360 Speaker 1: the pops in the freezer at the start of Monday morning, 290 00:16:04,760 --> 00:16:09,120 Speaker 1: and we're going to add a hidden camera. Okay, I 291 00:16:09,120 --> 00:16:10,680 Speaker 1: don't know where to get one of these if we 292 00:16:10,680 --> 00:16:12,680 Speaker 1: were to conduct such an experiment. I guess they're probably 293 00:16:12,680 --> 00:16:14,720 Speaker 1: pretty easy to yet. They probably have them in the 294 00:16:14,800 --> 00:16:19,760 Speaker 1: video department, yeah, everywhere. Yeah. So we're gonna hook up 295 00:16:19,760 --> 00:16:21,920 Speaker 1: the hidden camera, and then we're going to monitor the 296 00:16:21,960 --> 00:16:24,160 Speaker 1: camera and see what happens with the pops, who's taken them. 297 00:16:24,160 --> 00:16:26,760 Speaker 1: When we're gonna record the data, We're gonna record you 298 00:16:26,840 --> 00:16:29,920 Speaker 1: eating the pops. We're gonna record everything about the pops. Now, 299 00:16:29,920 --> 00:16:33,120 Speaker 1: we're also going to need a control group, right, Yeah, 300 00:16:33,160 --> 00:16:35,280 Speaker 1: I suppose we could we could have the control group. Yeah, 301 00:16:35,360 --> 00:16:38,239 Speaker 1: this is like when if you're testing a drug on people, 302 00:16:38,440 --> 00:16:41,720 Speaker 1: like in a clinical trial, like the test group would 303 00:16:41,800 --> 00:16:44,840 Speaker 1: receive a placebo or they would they would not receive 304 00:16:45,480 --> 00:16:48,440 Speaker 1: the proposed they proposed therapy, because you want to see 305 00:16:48,440 --> 00:16:51,320 Speaker 1: how people respond just normally. I do think we need 306 00:16:51,360 --> 00:16:54,960 Speaker 1: to do a podcast on the placebo effect, by the way, 307 00:16:53,600 --> 00:16:56,960 Speaker 1: I want to do one. Okay, so we're gonna also 308 00:16:57,040 --> 00:17:00,440 Speaker 1: place a box of pudding pops in the freeze by 309 00:17:00,560 --> 00:17:03,320 Speaker 1: the dev team, and that should be interesting because they 310 00:17:03,360 --> 00:17:05,800 Speaker 1: are a wacky bunch, yeah, and they're far away, you know, 311 00:17:06,320 --> 00:17:09,399 Speaker 1: like for the purposes of this experiment, Josh Clark never 312 00:17:09,440 --> 00:17:12,280 Speaker 1: goes there. And also for the purposes of this experiment, 313 00:17:12,320 --> 00:17:15,200 Speaker 1: the development team does not like putting their all allergic 314 00:17:15,240 --> 00:17:18,560 Speaker 1: to it. Okay, all right, all right, so they're a 315 00:17:18,560 --> 00:17:21,560 Speaker 1: good control group. Alright. So so yeah, we so we 316 00:17:21,600 --> 00:17:23,879 Speaker 1: carry out this experiment, right, Yeah, what do we find? 317 00:17:24,680 --> 00:17:26,240 Speaker 1: Get some data? Well, that's the thing. We have to 318 00:17:26,240 --> 00:17:31,960 Speaker 1: move on to step five, which is analyzed the data conclusion. Yeah, sure, 319 00:17:32,040 --> 00:17:38,679 Speaker 1: did do a little deduction deduction deducon So, for instance, 320 00:17:38,760 --> 00:17:41,960 Speaker 1: let's let's say that we look at the data and 321 00:17:42,600 --> 00:17:45,919 Speaker 1: it doesn't look like Josh's stealing these. It doesn't well, 322 00:17:46,000 --> 00:17:49,280 Speaker 1: let's say like Josh. Let's say that in the in 323 00:17:49,520 --> 00:17:53,160 Speaker 1: this particular footage, like Josh is only showing up at 324 00:17:53,240 --> 00:17:56,320 Speaker 1: in the at the freezer like like once a week, 325 00:17:56,840 --> 00:18:00,440 Speaker 1: and we're still having one a day disappear. So it's 326 00:18:00,440 --> 00:18:02,320 Speaker 1: not Josh. Yeah, so we would have to at this 327 00:18:02,400 --> 00:18:06,480 Speaker 1: point reject the hypothesis. Yes, and then we would have 328 00:18:06,560 --> 00:18:09,159 Speaker 1: to go backwards a few steps to the form of 329 00:18:09,240 --> 00:18:11,200 Speaker 1: hypothesis level, and we have to form a new one. 330 00:18:11,240 --> 00:18:14,120 Speaker 1: Maybe look into that black hole thing or maybe look 331 00:18:14,200 --> 00:18:16,960 Speaker 1: into the girls from I don't know, Stephane ms in 332 00:18:17,040 --> 00:18:19,399 Speaker 1: history class, right, Yeah, maybe they have a thing for 333 00:18:19,400 --> 00:18:23,280 Speaker 1: putting bops. Never know. And uh. And likewise, if we 334 00:18:23,280 --> 00:18:25,879 Speaker 1: were to look at the data and find proof that 335 00:18:26,000 --> 00:18:29,280 Speaker 1: Josh was actually stealing these, then we would have to 336 00:18:29,320 --> 00:18:32,600 Speaker 1: accept the hypothesis would be validated and it would be 337 00:18:32,680 --> 00:18:35,160 Speaker 1: nice and then maybe you know, submit it to Highlights 338 00:18:35,160 --> 00:18:38,879 Speaker 1: magazine for republication. Well, yes, of course you bring up 339 00:18:39,040 --> 00:18:42,040 Speaker 1: a good point. So after we're after we're done analyzing 340 00:18:42,040 --> 00:18:45,080 Speaker 1: the data and we've drawn conclusions and um, gone through 341 00:18:45,080 --> 00:18:48,159 Speaker 1: all the accepting or rejecting of the hypothesis. I'm not 342 00:18:48,160 --> 00:18:51,120 Speaker 1: even gonna get into the little hypothesis. Well, we're keeping 343 00:18:51,119 --> 00:18:55,160 Speaker 1: it pretty simple for for everybody here, right, So we're 344 00:18:55,160 --> 00:18:57,680 Speaker 1: gonna want to We're gonna want to communicate the results 345 00:18:57,720 --> 00:19:00,720 Speaker 1: of our experiment with our colleagues, with our fellow putting 346 00:19:00,760 --> 00:19:04,280 Speaker 1: pop scientists out there. We're gonna, you know, want to see, Hey, 347 00:19:04,359 --> 00:19:07,280 Speaker 1: what did you guys think about how we conducted our experiment. 348 00:19:07,320 --> 00:19:09,480 Speaker 1: Maybe we'll get maybe little submitted to highlights. So we 349 00:19:09,520 --> 00:19:12,040 Speaker 1: have to we have to go through peer review, and 350 00:19:12,600 --> 00:19:16,320 Speaker 1: one of the people who is a putting pop expert 351 00:19:16,359 --> 00:19:18,199 Speaker 1: will say, hey, you know what, actually I've done this 352 00:19:18,280 --> 00:19:21,520 Speaker 1: experiment and you forgot to do X y Z. You 353 00:19:21,520 --> 00:19:26,800 Speaker 1: didn't stick the camera in the right place because yeah, yeah, 354 00:19:27,320 --> 00:19:29,439 Speaker 1: or yeah. There are a number of problems that can 355 00:19:29,480 --> 00:19:31,600 Speaker 1: come and they come up constantly, like if you actually 356 00:19:31,600 --> 00:19:35,400 Speaker 1: look at any like peer reviewed publication, like it's constantly 357 00:19:35,440 --> 00:19:37,800 Speaker 1: like you know, people bringing up problems and just really 358 00:19:37,840 --> 00:19:40,600 Speaker 1: tearing into studies that they don't agree with, their find 359 00:19:40,600 --> 00:19:43,439 Speaker 1: fault with their disagree with the methods. Yeah, so there 360 00:19:43,440 --> 00:19:46,399 Speaker 1: are limitations to to science. It can't achieve everything, and 361 00:19:46,760 --> 00:19:49,760 Speaker 1: clearly the scientific method is a powerful tool. Um, but 362 00:19:49,840 --> 00:19:54,040 Speaker 1: it too has its limitations. For starters, a hypothesis has 363 00:19:54,080 --> 00:19:58,320 Speaker 1: to be testable and uh and falsifiable, and the experiments 364 00:19:58,320 --> 00:20:01,639 Speaker 1: and observations have to be repeatable. Yeah, so yeah, you 365 00:20:01,640 --> 00:20:03,400 Speaker 1: you can't do it like have an experiment. They can 366 00:20:03,400 --> 00:20:06,480 Speaker 1: only be done once. You can't do science in a vacuum, right, 367 00:20:06,600 --> 00:20:08,480 Speaker 1: um you well, I guess you could do science in 368 00:20:08,480 --> 00:20:10,240 Speaker 1: a vacuum, but that's you guys know what I meant. Yeah, 369 00:20:10,240 --> 00:20:11,840 Speaker 1: and it has to be testable, like you can't be 370 00:20:12,200 --> 00:20:15,280 Speaker 1: you know, nobody can have like a scientific experiment for 371 00:20:15,560 --> 00:20:18,400 Speaker 1: is there a God? Because that's just that's not testable. 372 00:20:18,440 --> 00:20:22,240 Speaker 1: It's it's not something that is you know, that's scientifically 373 00:20:22,359 --> 00:20:24,800 Speaker 1: provable or disprovable. Well, I can't believe we went from 374 00:20:24,800 --> 00:20:27,480 Speaker 1: putting pops to God and like the span of five minutes. Well, 375 00:20:27,520 --> 00:20:30,280 Speaker 1: someone say the distance is not that far, you know, 376 00:20:31,160 --> 00:20:35,359 Speaker 1: especially fans of pudding pops. I guess yeah. And sometimes 377 00:20:35,359 --> 00:20:38,280 Speaker 1: you have instances where scientific principles are used to try 378 00:20:38,320 --> 00:20:41,960 Speaker 1: to lend credibility to certain non scientific ideas. Yeah. Like 379 00:20:42,440 --> 00:20:46,320 Speaker 1: let's say, for instance, I were to have the bones 380 00:20:46,359 --> 00:20:50,159 Speaker 1: of some like you know older you know, hominid that 381 00:20:50,600 --> 00:20:52,439 Speaker 1: may have you know, evolved and do a human and 382 00:20:52,480 --> 00:20:53,959 Speaker 1: I tried to make the case that this is an 383 00:20:53,960 --> 00:20:56,960 Speaker 1: alien skeleton, you know, and you know, and I like 384 00:20:57,040 --> 00:21:01,480 Speaker 1: sort of applied some sort of pseudo scientific ideas. You know, 385 00:21:01,520 --> 00:21:03,280 Speaker 1: people do this all the time where you kind of 386 00:21:03,320 --> 00:21:06,240 Speaker 1: like take like a one scoop of science and one 387 00:21:06,240 --> 00:21:10,600 Speaker 1: scoop of crazy and or one scoop of just extreme bias, 388 00:21:10,680 --> 00:21:13,840 Speaker 1: and you know, mix the two and you know, produce 389 00:21:13,960 --> 00:21:15,679 Speaker 1: this cake that a lot of people think is the 390 00:21:15,680 --> 00:21:18,320 Speaker 1: real deal. Which is why everybody should be educated in science. 391 00:21:18,359 --> 00:21:20,920 Speaker 1: Everybody should have the tools to apply their their critical 392 00:21:20,920 --> 00:21:25,040 Speaker 1: thinking skills to a particular uh scientific problem or a 393 00:21:25,080 --> 00:21:29,080 Speaker 1: scientific paper them right, and likewise, I mean, anything in 394 00:21:29,119 --> 00:21:31,800 Speaker 1: science should be uh, I mean it should be just 395 00:21:31,880 --> 00:21:35,480 Speaker 1: fair game for for criticism, provided you know, bring the 396 00:21:35,480 --> 00:21:38,600 Speaker 1: science the science. Science is a tool that continually, you know, 397 00:21:38,720 --> 00:21:42,200 Speaker 1: changes what we believe about the universe, you know, and 398 00:21:42,200 --> 00:21:44,760 Speaker 1: and it's you know, nothing nothing is sacred, you know, 399 00:21:45,440 --> 00:21:48,000 Speaker 1: use the tools of science to question what has come before, 400 00:21:48,760 --> 00:21:50,960 Speaker 1: no doubt, no doubt. That seems like a pretty good 401 00:21:50,960 --> 00:21:53,520 Speaker 1: place to end. So, um, we hope you've enjoyed our 402 00:21:53,560 --> 00:21:57,679 Speaker 1: walk through, uh the scientific method and are putting pop experiment, 403 00:21:57,720 --> 00:21:59,760 Speaker 1: and we hope you buy a big box of putting 404 00:21:59,760 --> 00:22:02,920 Speaker 1: pop right after this, right, and again, the pudding pop 405 00:22:03,359 --> 00:22:07,159 Speaker 1: example is it's pretty simple. It's we're just trying to 406 00:22:07,640 --> 00:22:11,200 Speaker 1: basic structure out there for the scientist. So let's turn 407 00:22:11,240 --> 00:22:14,119 Speaker 1: to something different, a little listener mail. Yeah, you have 408 00:22:14,119 --> 00:22:23,119 Speaker 1: some listener mail there for us, I do. Okay, So 409 00:22:23,160 --> 00:22:25,080 Speaker 1: here goes a while back, and maybe you guys will 410 00:22:25,119 --> 00:22:27,760 Speaker 1: remember that we covered oil in a two part series 411 00:22:28,280 --> 00:22:32,520 Speaker 1: about looking for it and then harvesting it from the earth. Yeah, yep, 412 00:22:32,920 --> 00:22:35,040 Speaker 1: And we put the call out for people who have 413 00:22:35,080 --> 00:22:37,280 Speaker 1: worked on oil rigs to let us know how that was. 414 00:22:37,359 --> 00:22:40,840 Speaker 1: And sure enough we got somebody who responded, Thank you, Adam. 415 00:22:40,880 --> 00:22:45,000 Speaker 1: And Adam sent us a pretty interesting note. So he says, hey, guys, 416 00:22:45,320 --> 00:22:47,720 Speaker 1: I love the podcast. You did a great job summarizing 417 00:22:47,720 --> 00:22:50,720 Speaker 1: both the addiction and how oil is explored. Slash produced. 418 00:22:51,160 --> 00:22:53,120 Speaker 1: I've worked in the oil industry for a few years 419 00:22:53,160 --> 00:22:56,639 Speaker 1: after graduating as an electrical engineer from Ohiouse State. Go Bucks. 420 00:22:57,800 --> 00:23:02,000 Speaker 1: That's in the email. Okay, you mentioned one of the 421 00:23:02,040 --> 00:23:05,040 Speaker 1: things I used to do on the podcast, controlled explosions 422 00:23:05,040 --> 00:23:07,600 Speaker 1: through the casing to facilitate the flow of oil gas 423 00:23:07,600 --> 00:23:10,720 Speaker 1: into a newly drilled well. He also used to run 424 00:23:10,880 --> 00:23:12,800 Speaker 1: a variety of tools into the well to help oil 425 00:23:12,840 --> 00:23:16,120 Speaker 1: companies produce their wells more efficiently, from checking for plaque 426 00:23:16,119 --> 00:23:18,800 Speaker 1: along the casing that minimizes diameter, to see if one 427 00:23:18,880 --> 00:23:21,719 Speaker 1: zone of production might be producing too much water. So 428 00:23:21,760 --> 00:23:24,080 Speaker 1: all sorts of really interesting stuff around there. And then 429 00:23:24,200 --> 00:23:28,560 Speaker 1: Adam goes on to add oil rigs are not luxurious. 430 00:23:28,800 --> 00:23:32,320 Speaker 1: They have minimal space used as efficiently as possible. I 431 00:23:32,320 --> 00:23:34,760 Speaker 1: was on jack Off riggs in the Middle East, the 432 00:23:35,040 --> 00:23:38,280 Speaker 1: United Arab Emirates and Qatar, so that's my reference point. 433 00:23:38,520 --> 00:23:41,560 Speaker 1: Maybe it's different in other parts of the world. None 434 00:23:41,560 --> 00:23:43,680 Speaker 1: of them many rigs. I worked on how to gym 435 00:23:43,800 --> 00:23:46,080 Speaker 1: if people wanted to exercise, they could walk in circles 436 00:23:46,080 --> 00:23:50,800 Speaker 1: on the heliport. It's true there were quote unquote chefs 437 00:23:50,840 --> 00:23:54,000 Speaker 1: and quote unquote doctors, but they didn't exactly have Culinary 438 00:23:54,000 --> 00:23:58,240 Speaker 1: Institute diplomas or Envy certificates hanging on the walls. Platforms, 439 00:23:58,280 --> 00:24:01,080 Speaker 1: on the other hand, are like a small city and 440 00:24:01,119 --> 00:24:04,159 Speaker 1: these amenities are common. So if you're a work at 441 00:24:04,240 --> 00:24:06,240 Speaker 1: fiend and you're interested in working for oil, I guess 442 00:24:06,320 --> 00:24:08,159 Speaker 1: platforms would be the way to go. I like the 443 00:24:08,200 --> 00:24:13,439 Speaker 1: idea that the doctors had culinary diploma shows not what 444 00:24:13,520 --> 00:24:16,359 Speaker 1: he was saying. So, Adam, ads um, these platforms are 445 00:24:16,359 --> 00:24:18,760 Speaker 1: there for the long haul and they're designed to be livable. Also, 446 00:24:18,840 --> 00:24:21,000 Speaker 1: in most areas of the world, the production is taken 447 00:24:21,000 --> 00:24:24,200 Speaker 1: over by the national oil company. Thus the platform mainly 448 00:24:24,200 --> 00:24:27,160 Speaker 1: houses workers from that country, or at least that country's 449 00:24:27,160 --> 00:24:31,280 Speaker 1: oil company's staff. During the drilling process. The oil company 450 00:24:31,359 --> 00:24:34,719 Speaker 1: represent may represent one the personnel on the rig at 451 00:24:34,720 --> 00:24:36,960 Speaker 1: any given time. He said us a picture of him 452 00:24:36,960 --> 00:24:39,800 Speaker 1: on a rig, and he's a he's behind an exclusive 453 00:24:39,840 --> 00:24:42,800 Speaker 1: sign with a white hard hat. Did you see it? No? 454 00:24:42,880 --> 00:24:45,879 Speaker 1: I didn't. I'll have to pick it up, so he 455 00:24:45,920 --> 00:24:48,480 Speaker 1: writes on I no longer work in the industry, thankfully. 456 00:24:48,480 --> 00:24:50,199 Speaker 1: As you mentioned, the pay is excellent and the benefits 457 00:24:50,240 --> 00:24:52,680 Speaker 1: are good, depending on who you work for. The oil 458 00:24:52,680 --> 00:24:56,159 Speaker 1: service companies typically paid better but treated employees worse. I 459 00:24:56,200 --> 00:24:58,200 Speaker 1: took the money I made and did an MBA at 460 00:24:58,200 --> 00:25:01,560 Speaker 1: a top ten business school in Spain. Adam, and we'll 461 00:25:01,600 --> 00:25:04,359 Speaker 1: actually start my first post NBA job next week at 462 00:25:04,359 --> 00:25:08,040 Speaker 1: a wind turbine company in Denmark. Well that's interesting into 463 00:25:08,080 --> 00:25:11,120 Speaker 1: the story. Well, yeah, so he says, this is the close. Yes, 464 00:25:11,200 --> 00:25:13,400 Speaker 1: working in the oil industry fueled my passion to get 465 00:25:13,400 --> 00:25:15,960 Speaker 1: into renew the energy. I think anyone involved in the 466 00:25:16,000 --> 00:25:19,159 Speaker 1: process can see how unsustainable it is. I hope you 467 00:25:19,160 --> 00:25:22,280 Speaker 1: found this martually interesting. We did. We totally did. Thank 468 00:25:22,320 --> 00:25:25,440 Speaker 1: you really, thanks a ton for writing Adam. Yeah, I mean, 469 00:25:25,520 --> 00:25:28,320 Speaker 1: even if it is unsustainable, certainly, And you know, a 470 00:25:28,400 --> 00:25:30,639 Speaker 1: lot of opinions vary about the about the use of 471 00:25:30,680 --> 00:25:32,879 Speaker 1: oil and the oil industry in general. But as we 472 00:25:32,920 --> 00:25:36,159 Speaker 1: mentioned that the actual podcast, the process involved in finding 473 00:25:36,160 --> 00:25:38,160 Speaker 1: the oil and then extracting it, it's just just really 474 00:25:38,160 --> 00:25:41,440 Speaker 1: fascinating because, like we say, if you're when someone is 475 00:25:41,440 --> 00:25:44,080 Speaker 1: addicted to something, they'll go to extraordinary means to get 476 00:25:44,160 --> 00:25:46,960 Speaker 1: what they're addicted to and um, and we go to 477 00:25:47,000 --> 00:25:49,560 Speaker 1: extraordinary means to get that oil. And it's it's really 478 00:25:49,600 --> 00:25:53,800 Speaker 1: amazing because there's some cold, just excellent technology involved in it. Yeah, 479 00:25:53,840 --> 00:25:56,800 Speaker 1: it's excellent minds. So hey, if you guys have any 480 00:25:56,800 --> 00:25:58,440 Speaker 1: thoughts that you want to send us, whether they're about 481 00:25:58,440 --> 00:26:01,840 Speaker 1: oil or the scientific method it um or putting bops, 482 00:26:02,400 --> 00:26:04,160 Speaker 1: do this an email at science Stuff at how stuff 483 00:26:04,440 --> 00:26:08,000 Speaker 1: dot com or connect with us. We're on Facebook, stuff 484 00:26:08,000 --> 00:26:10,680 Speaker 1: from the Science Lab or Twitter, were Lab stuff. Yeah, 485 00:26:10,720 --> 00:26:14,120 Speaker 1: we'll constantly update you on what we're podcasting about, blogging about. 486 00:26:14,160 --> 00:26:16,800 Speaker 1: And also just like I looked out dated, which just 487 00:26:16,800 --> 00:26:20,760 Speaker 1: cool science stuff that I find on the web. So 488 00:26:20,840 --> 00:26:23,119 Speaker 1: look us up and thanks for listening, guys, we appreciate it. 489 00:26:30,200 --> 00:26:32,600 Speaker 1: For more on this and thousands of other topics, does 490 00:26:32,640 --> 00:26:36,159 Speaker 1: it how stuff works dot com. Want more how stuff works, 491 00:26:36,440 --> 00:26:38,560 Speaker 1: check out our blogs on the house stuff works dot 492 00:26:38,640 --> 00:26:45,760 Speaker 1: com home page.