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Political pollsters are pretending they know what's happening. They don't.1 month ago in Genomics, Medicine, and Pseudoscience
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Course Corrections6 months ago in Angry by Choice
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The Site is Dead, Long Live the Site2 years ago in Catalogue of Organisms
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The Site is Dead, Long Live the Site2 years ago in Variety of Life
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Does mathematics carry human biases?4 years ago in PLEKTIX
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A New Placodont from the Late Triassic of China5 years ago in Chinleana
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Posted: July 22, 2018 at 03:03PM6 years ago in Field Notes
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Bryophyte Herbarium Survey7 years ago in Moss Plants and More
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Harnessing innate immunity to cure HIV8 years ago in Rule of 6ix
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WE MOVED!8 years ago in Games with Words
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post doc job opportunity on ribosome biochemistry!9 years ago in Protein Evolution and Other Musings
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Growing the kidney: re-blogged from Science Bitez9 years ago in The View from a Microbiologist
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Blogging Microbes- Communicating Microbiology to Netizens10 years ago in Memoirs of a Defective Brain
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The Lure of the Obscure? Guest Post by Frank Stahl12 years ago in Sex, Genes & Evolution
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Lab Rat Moving House13 years ago in Life of a Lab Rat
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Goodbye FoS, thanks for all the laughs13 years ago in Disease Prone
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Slideshow of NASA's Stardust-NExT Mission Comet Tempel 1 Flyby13 years ago in The Large Picture Blog
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in The Biology Files
Having green in your flag is bad for your IQ
Important update 7/21-15: Please see comments below on the really low quality of the data. I was originally serious about this analysis taking the IQ data at face value, but now want to state that while I do find the aspect of the flag colors amusing, I totally do not trust the IQ data.
If your country has green in its flag, then you are less likely to be intelligent.
If that isn't an explosive statement, then I don't know what is. But data from Raven-online suggest that this is true.
In this figure is 183 countries ranked by average IQ from left to right. The higher average IQ the further to the right they are plotted. Countries that have green in their flags have a green spot, and all other have a red spot:
The average IQ of countries with green flags is 79.2 (stdev=9.5) and of countries no no green it is 89.0 (stdev=10.1), and this difference is statistically significant (a 2-sample t-test gives p=2.29e-10). You can download the annotated data here.
Supposedly Raven's test-results are pretty good:
They are implying that if you have high IQ, then you have a higher the chance that you can successfully attain a higher educational degree. But look at the top ranked countries: Italy has some green in their flag and an average IQ score of 102. The countries ranked higher than Italy are Hong Kong, Singapore, South Korea, Japan, and Taiwan - all affluent Asian nations that emphasize book-studies from a very young age. Many, if not all, of these countries make middle-schoolers take tests, and these tests matter for their future. They are, in other words, trained to take tests. Their school systems are good at making students do well on tests. Compare that to poor counties like Djibouti, Lesotho, Gabon, and Equatorial Guinea, who all have green in their flags. They are poor countries, which obviously negatively affects education, which then doesn't allow children to practice taking tests very much (which I am not particularly in favor of anyway, I have to say).
You can practice taking tests, and it will affect your score. If that wasn't true, then there would be no point in practicing taking tests, which is something teachers everywhere make their students do.
So rather than IQ affecting education, I posit that it is education that affects IQ. That doesn't sound nearly as sexy (nor is it novel), and Raven is in business of selling IQ tests. They would like IQ to say something about your chances in life, whereas the truth is more likely that the more chances you
have in life, the higher your IQ is likely to be.
The really interesting question here is what causes the correlation between average national IQ and having green in the flag. You could very well argue that it's completely spurious: just because there isa correlation does not necessitate that there is any causation. It is difficult to argue against such a proposition - there exists lots of very intriguing but probably completely random correlations, such as yearly deaths by drowning in a pool vs. the number of movies Nicholas Cage has appeared in. However, those strange and unexplainable correlations are found by cherry-picking many, many more random pairs of variables. The correlation between IQ and green in flag is a one-shot observation, which makes it stand out. The task is then to come up with plausible explanations for the relationship.
Start by noting that there is a positive correlation between national income, education, and average IQ. It makes sense. We then observe that having green in the flag increases IQ: "smarter people dislike green". Maybe there is an effect of having green in the flag on national income: "green makes people lazy" or "other counties prefer not to trade with 'green' countries":
Other variables could be introduced. It seems to me that the "green" countries are for the most part warmer countries, particularly African. The closer countries are to the equator (lower latitude), the worse the average IQ is. Perhaps something about the latitude causes lower national income (Jared Diamond argue that coincidental geography is the main factor in explaining differences in national wealth among countries) and a preference for green? How about this: "people who live in environments where plants are green all year round are more likely to make their flags contain some green". It could be some other psychological preference that is shaped by living at a lower latitude.
I am stumped. Maybe some historian would have something to say about the prevalence of green flags at lower latitudes?
Here's more from Raven's website (original emphasis):
However, there's probably little doubt that having an educated population does contributes to the national wealth, so causality is likely circular: wealth → education → wealth, with higher average IQ (i.e., test-taking abilities) as a side-effect.
If your country has green in its flag, then you are less likely to be intelligent.
If that isn't an explosive statement, then I don't know what is. But data from Raven-online suggest that this is true.
In this figure is 183 countries ranked by average IQ from left to right. The higher average IQ the further to the right they are plotted. Countries that have green in their flags have a green spot, and all other have a red spot:
The average IQ of countries with green flags is 79.2 (stdev=9.5) and of countries no no green it is 89.0 (stdev=10.1), and this difference is statistically significant (a 2-sample t-test gives p=2.29e-10). You can download the annotated data here.
Supposedly Raven's test-results are pretty good:
It has been demonstrated that there is a 70% correlation between the results of this test and educational achievement. Consequently, the higher your result in this test the greater your chances of success at higher levels of study. By comparison, the correlation factors in other IQ tests have an average variation of between 20 and 60%.70% is a very strong correlation, and they are probably right to point out that the strong correlation between IQ and level of education is not spurious. And yet, I think they got causality the wrong way around.
They are implying that if you have high IQ, then you have a higher the chance that you can successfully attain a higher educational degree. But look at the top ranked countries: Italy has some green in their flag and an average IQ score of 102. The countries ranked higher than Italy are Hong Kong, Singapore, South Korea, Japan, and Taiwan - all affluent Asian nations that emphasize book-studies from a very young age. Many, if not all, of these countries make middle-schoolers take tests, and these tests matter for their future. They are, in other words, trained to take tests. Their school systems are good at making students do well on tests. Compare that to poor counties like Djibouti, Lesotho, Gabon, and Equatorial Guinea, who all have green in their flags. They are poor countries, which obviously negatively affects education, which then doesn't allow children to practice taking tests very much (which I am not particularly in favor of anyway, I have to say).
You can practice taking tests, and it will affect your score. If that wasn't true, then there would be no point in practicing taking tests, which is something teachers everywhere make their students do.
So rather than IQ affecting education, I posit that it is education that affects IQ. That doesn't sound nearly as sexy (nor is it novel), and Raven is in business of selling IQ tests. They would like IQ to say something about your chances in life, whereas the truth is more likely that the more chances you
have in life, the higher your IQ is likely to be.
The really interesting question here is what causes the correlation between average national IQ and having green in the flag. You could very well argue that it's completely spurious: just because there isa correlation does not necessitate that there is any causation. It is difficult to argue against such a proposition - there exists lots of very intriguing but probably completely random correlations, such as yearly deaths by drowning in a pool vs. the number of movies Nicholas Cage has appeared in. However, those strange and unexplainable correlations are found by cherry-picking many, many more random pairs of variables. The correlation between IQ and green in flag is a one-shot observation, which makes it stand out. The task is then to come up with plausible explanations for the relationship.
Start by noting that there is a positive correlation between national income, education, and average IQ. It makes sense. We then observe that having green in the flag increases IQ: "smarter people dislike green". Maybe there is an effect of having green in the flag on national income: "green makes people lazy" or "other counties prefer not to trade with 'green' countries":
Other variables could be introduced. It seems to me that the "green" countries are for the most part warmer countries, particularly African. The closer countries are to the equator (lower latitude), the worse the average IQ is. Perhaps something about the latitude causes lower national income (Jared Diamond argue that coincidental geography is the main factor in explaining differences in national wealth among countries) and a preference for green? How about this: "people who live in environments where plants are green all year round are more likely to make their flags contain some green". It could be some other psychological preference that is shaped by living at a lower latitude.
I am stumped. Maybe some historian would have something to say about the prevalence of green flags at lower latitudes?
Here's more from Raven's website (original emphasis):
Richard and Tatu argues that differences in national income are correlated with differences in the average national intelligence quotient (IQ). They further argue that differences in average national IQs constitute one important factor, but not the only one, contributing to differences in national wealth and rates of economic growth.I ask again: do differences in average national IQ scores contribute to national wealth and economic growth, or is is more likely that national wealth contribute to raising the national average IQ? I'd say the latter, contrary to Richard and Tatu.
These results are controversial and have caused much debate, they must be interpreted with extreme caution.
Sources: IQ and the Wealth of Nations (2006), IQ and Global Inequality (2002)
However, there's probably little doubt that having an educated population does contributes to the national wealth, so causality is likely circular: wealth → education → wealth, with higher average IQ (i.e., test-taking abilities) as a side-effect.
Ken Ham's solution to accomodationism and secular humanism
Ken Ham (founder and president of Answers in Genesis, the Creation Museum, wannabe arc builder) is a Young Earth creationist, and he prides himself in taking everything in the Bible literally. AiG even says that they don't interpret the Bible, they "just read it", which is of course a load of hogwash, as everything is written interpreted in some way (for example from other languages to English!).
I agree with him on two points, but then I think that's it: that it makes no sense to pick and choose which parts of the Bible to take literally, and that he is entitled to his beliefs. How can we know which parts of the Bible are allegory and which stories really happened? I think we can't. Ham's and my solution are just completely opposite, as I choose to believe that everything in the Bible is written by man.
And on the latter agreement, he can believe what he wants. I just wish he would keep it to himself, because I think his beliefs are really bad for society. I don't object to his beliefs merely because I can. I don't bash him and AiG just because I have a right to do so, but because they are demonstratively making things worse for us all. Creationism, global climate change denial, anti-science, anti-rationality, anti-education, etc.
I write this because many people, Christians and atheists alike, are accomodationists. They believe there need not be a conflict between religion and science. They often point to prominent scientists who are/were religious (Francis Collins, Kenneth Miller, Isaac Newton, etc.). But that these people manage(d) to reconcile their faith with scientific facts doesn't mean that it is a logically consistent position. They have merely succeeded in compartmentalizing these two spheres of knowledge so they don't overlap.
Additionally, accomodationists can defend their position till kingdom come, but meanwhile a majority of American Christians fail to reconcile their faith with science, and that is a huge problem. Many are more aligned with Ken Ham than with the accomodationists. 42 percent of Americans are outright creationists, while another 31 percent looks like some sort of accomodationists, and only (though rising) 19 percent believe that God had nothing to do with creation (you know, the actual, sane conclusion based on evidence):
http://www.gallup.com/poll/170822/believe-creationist-view-human-origins.aspx |
How long does it take to lose a culture, from a Christian perspective?Nice one, Ken! Quoting Hitler right in the beginning.
Actually, it takes only one generation.
The devil knows this, and of course God warns us about it. Adolf Hitler understood this when he said, “He alone, who owns the youth, gains the future!”
I think one of the saddest pages in the Bible is in Judges 2:10–12, “When all that generation had been gathered to their fathers, another generation arose after them who did not know the Lord nor the work which He had done for Israel. Then the children of Israel . . . forsook the Lord God of their fathers, who had brought them out of the land of Egypt; and they followed other gods from among the gods of the people who were all around them.”Really?! That's one of the saddest passages in the Bible? How about the flood, when most humans and animals perished? What about when the LORD sent two bears to maul 42 kids?
24 He turned around, looked at them and called down a curse on them in the name of the Lord. Then two bears came out of the woods and mauled forty-two of the boys.2 Kings 2:24
But yes, I understand his sadness nonetheless. Ken is sad because children today are leaving the church, and that is all he really cares about.
Obviously the parents in Joshua’s day did not teach their children as they should have—and in one generation, the devil had those kids! While it’s ultimately a matter of God’s grace that anyone is saved, God has given parents an immense responsibility to do their part. Over and over again, the Jewish fathers were told about their crucial role but they shirked it (see Psalm 78).Here is the eternal dichotomy that is such a huge problem for Christianity, but which is always ignored: if God is omnipotent, why does he need our help? Why doesn't he just make it so? If he gives us free will, how can he know everything? And why did he need to torture his own son in order to forgive us for our sins? Why doesn't he just forgive us like normal people forgive each other without the barbary?
The answer is of course that those stories were made up by frightened humans, and it is not a compelling story to just have God forgive us all and make everything nice and rosy.
The public schools have been teaching their own brand of apologetics: how to defend the idea of evolution and history over millions of years, thus causing multitudes of U.S. students from Christian homes to doubt the history in Genesis. Doubts about Genesis place young people on a slippery slide of unbelief that eventually destroys their confidence in the rest of Scripture. Their trust in the soul-saving gospel itself, which is grounded on the Bible’s historical claims, is undermined.Completely true. I think that is exactly how it works. Education and information is what will erode creationist beliefs, because while religion does not imply creationism, creationism does imply religion. Creationism come only from religion. The accomodationist view is a fallacious one, and the inevitable result is that more and more new adults will realize how problematic it is to reconcile the actual contradictions between scripture and scientific facts, as well as the contradictory ways of understanding the world around us, one being based on evidence and the other on faith (i.e., arbitrary beliefs contrary to evidence).
Yes, the atheists, like Hitler and Stalin, know that if they can capture the next generation (through the education system, media, etc.), they will have the culture.Hitler was Catholic. And yes, the culture will be shaped by the coming generations, of course. We all know this, and there is nothing nefarious about wanting to educate our children the best way possible. Science in science classes. Religion in history(?) classes. All of the religions. Go teach your sheep whatever you want in your own churches, but keep church and state separate in the public sphere. Also, tax the churches.
So what is Ken Ham's solution?
Teaching young people how God’s Word—rather than the atheistic worldview—makes sense of our world requires intense study, commitment, and fervent prayer on our parts. The church and parents must reevaluate their old assumptions about the way we should be teaching our kids in a hostile culture, and work together to build the next generation by following the directives from God’s Word.In other words, shield your children from the evil ways of the secular humanists. Teach your kids apologetics. I am pleased to see that Ken Ham really has no new answer to his problem. I'll give him one, though: remove the First Amendment, teach only the one true religion in public schools, shut down the internet, build a theocracy. That will really make your problem go away, because the next generations would then be ignorant of how the world actually works. Move to Saudi Arabia, Ken.
Imagine what would happen if God’s people raised up generations of kids who knew what they believed concerning the Christian faith, why they believe, and how to defend that faith against the secular attacks of the day. They could then proclaim the gospel with authority because they believed the authority upon which it stands. We would change the world!
American teens are losing their religion
Just this figure.
Fig 2. Percentage of American adolescents endorsing “none” for religious affiliation, 1966–2014.
From Twenge et al. (2015) Generational and Time Period Differences in American Adolescents’ Religious Orientation, 1966–2014, PLoS ONE.
Press release
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Fig 2. Percentage of American adolescents endorsing “none” for religious affiliation, 1966–2014.
From Twenge et al. (2015) Generational and Time Period Differences in American Adolescents’ Religious Orientation, 1966–2014, PLoS ONE.
Press release
\o/
The Monty Hall Evolver
The Monty Hall problem is very famous (Wikipedia, NYT). It is so famous because it so easily fools almost everyone the first time they hear about it, including people with doctorate degrees in various STEM fields.
There are three doors. Behind one is a big prize, a car, and behind the two others are goats. The contestant first picks one door without opening it. Then the game show host tells you that he will open one of the other two doors behind which there is a goat. It is assumed (but often untold) that the host knows where the car is, and so deliberately opens a door with a goat behind it. It is also assumed that the contestant wants to win the car, but let me tell you already that if you really want a goat, you can be sure to get one. Then the contestant is given the choice of choosing again. Since there are now two closed doors, the choices are to stay on the door first chosen or to switch to the only other closed door. The question is what the best strategy is, switching or staying. Is the probability of getting the car 50% for staying and switching? No, it turns out that switching is the best strategy, giving the contestant a 2 in 3 chance of winning the car. Why? Well, there are many ways to realize this. My favorite is this. Once the contestant has chosen one door, we know that the chance the car is behind it is 1/3. Thus, the chance it’s behind one of the two others is 2/3. Because the host opens one of the two other doors, switching is equivalent to actually choosing two doors, giving a 2 in 3 chance of getting the car. There we go. Another way to arrive at this (correct) result is to actually do it many times over. Pick three cards, a red (the car) and two black (the goats), and have someone play the host. Do this say 100 times, and you’ll see that if you switch every time, you’ll get in the neighborhood of 67 red car(d)s. However, I give it a pretty good chance that if you do this, then after playing a handful of times you’ll anyway realize that the solution of course is 2/3 for switching.
I once many years ago set out to write a code to do the experiment. I would write the code, run it a kadoolian times and expect to see the switching strategy win out two thirds of a kadoolian times. However, much to my surprise, when I started writing the code, if-statements and all, the solution became so glaringly obvious that I gave up doing it. It just seemed so futile at that point. I suspect that my hankering for using simulations to investigate problems was strongly influenced by this experience.
Recently I have introduced several people to the Monty Hall problem - always a great party trick. And again, almost everyone instantly arrives at 50/50, and are as adamant that this is the correct solution as the next guy. So I decided to finally write the code to do it, but made two stipulations: 1) the code must mirror the way the problem is told as closely as possible. This will not be the most efficient code to write or the fastest to execute, but will hopefully be easy for readers to see through, so to speak. And 2) rather than just playing the game many times, I will let a population of individuals play it and compete with each other for a chance to reproduce (aka evolution). For full disclosure, the code is included below.
The Monty Hall code
The evolutionary dynamics
The objective of the organisms is to come up with the best strategy for playing the Monty Hall game. Each organism has just one “gene”, called MH01, and this gene determines the probability that when playing the game the organism chooses to stay or to switch. The value of MH01 is a number between 0 and 1. If the number is 0, the organism never switches door, and if it is 1, then the organism always switches, and if the value is, say, 0.4825, then there is a 48.25 percent chance that the organism switches door. Easy-peasy.
We do two experiments: 1) comparing two strategies (50% switching vs. 50% staying, or MH01=0 vs. MH01 = 1) without mutations, and 2) starting all individuals with MH01=0 and adding mutations to all offspring.
We start with a population of N=100 individual organisms. One organism is chosen at random among the N individuals to play the game. If it wins it gets to reproduce. In that case a copy of it now replaces one of the N organisms chosen at random (including its parent). Nothing happens if they lose the game. This results in a constant population size and overlapping generations. When an offspring replaces a hapless individual, the MH01 gene can mutate (in experiment 2). This results in MH01 increasing or decreasing by a small uniformly random value. And that’s it.
The evolved solution
Figure 1: Starting with 50% switchers (MH01=1) and 50% stayers (MH01=0) all ten simulation runs result in the switchers outcompeting the stayers. Switchers win the Monty Hall game twice as often, and the population frequency of MH01=1 thus stochastically increases until it reaches 100% (fixation). Population size is N=100 (the five runs that reach a frequency of 1 after about 1,000 plays) and N=500 (five runs that take about 10,000 plays to go to fixation).
Figure 2: Average population value of MH01 with large-effect mutations. Starting with 100% stayers (MH0=0). MH01 increases relatively fast, reaching the largest value after around 30,000 plays. The effect of mutations is uniformly distributed on the interval ±0.05 centered on the current value. Population size is N=100. The black lines are minimum (bottom) and maximum (top) values of MH01 in the population.
Figure 3: Average population value of MH01 with small-effect mutations. Starting with 100% stayers (MH0=0). MH01 increases relatively slowly, reaching the largest value after around 250,000 plays. The effect of mutations is uniformly distributed on the interval ±0.01 centered on the current value. Population size is N=100. The black lines are minimum (bottom) and maximum (top) values of MH01 in the population. There is less variation in MH01 in this case because the effect of mutations is lower than in the runs shown in figure 2.
Discussion
What a relief! When running simulations like this there is always the risk that for some unseen reason the evolved solution is different from what you anticipated. Thankfully that is not the case here: evolution favors the fittest organisms, and the fittest organisms are those that tend to switch when they play the game. Success!
Why does MH01 not go to fixation? In other words, why does the average population value of MH01 (blue lines) not become 1? The answer is that there is a mutational load (Wikipedia) caused by the effect of mutations. Offspring of a parent with MH01=1 has a 50% chance of having a lower value of MH01, so there will always be some individuals with a suboptimal value of MH01. What is increased in evolutionary dynamics is not fitness but free fitness. Free fitness is the sum of the logarithm of fitness and an entropy term that is non-zero when there is either mutation and/or drift. The term was introduced by Yoh Iwasa in 1988: Free fitness that always increases in evolution.
Let me reiterate that the answer of 2/3 chance to get the car when switching relies on the game host knowing where the car is, and deliberately opening a door that the contestant has not chosen and where there is a goat behind. If the host opens another door at random and there happens to be a goat behind it, then the probability of getting the car is only 50% for switching (and for staying).The probability is thus dependent on the knowledge that the contestant has about the knowledge and intent of the host. Only if the contestant knows that the host knows what he is doing does the chance increase by switching. Update 7/15/2015: I was wrong about the effect of the knowledge of the contestant about what the host knows. It makes no difference what the contestant knows about what the host knows. If the host knows what he is doing, then the chance of winning by switching is 2/3 no matter what. Otherwise this simulation would not work, as the computer doesn't "know" anything. A simple enumeration of the possible outcomes makes this abundantly clear, as seen below in the comments.
You can play the Monty Hall game here, where you can also play the version where the host does not know which door has the car.
There are three doors. Behind one is a big prize, a car, and behind the two others are goats. The contestant first picks one door without opening it. Then the game show host tells you that he will open one of the other two doors behind which there is a goat. It is assumed (but often untold) that the host knows where the car is, and so deliberately opens a door with a goat behind it. It is also assumed that the contestant wants to win the car, but let me tell you already that if you really want a goat, you can be sure to get one. Then the contestant is given the choice of choosing again. Since there are now two closed doors, the choices are to stay on the door first chosen or to switch to the only other closed door. The question is what the best strategy is, switching or staying. Is the probability of getting the car 50% for staying and switching? No, it turns out that switching is the best strategy, giving the contestant a 2 in 3 chance of winning the car. Why? Well, there are many ways to realize this. My favorite is this. Once the contestant has chosen one door, we know that the chance the car is behind it is 1/3. Thus, the chance it’s behind one of the two others is 2/3. Because the host opens one of the two other doors, switching is equivalent to actually choosing two doors, giving a 2 in 3 chance of getting the car. There we go. Another way to arrive at this (correct) result is to actually do it many times over. Pick three cards, a red (the car) and two black (the goats), and have someone play the host. Do this say 100 times, and you’ll see that if you switch every time, you’ll get in the neighborhood of 67 red car(d)s. However, I give it a pretty good chance that if you do this, then after playing a handful of times you’ll anyway realize that the solution of course is 2/3 for switching.
I once many years ago set out to write a code to do the experiment. I would write the code, run it a kadoolian times and expect to see the switching strategy win out two thirds of a kadoolian times. However, much to my surprise, when I started writing the code, if-statements and all, the solution became so glaringly obvious that I gave up doing it. It just seemed so futile at that point. I suspect that my hankering for using simulations to investigate problems was strongly influenced by this experience.
Recently I have introduced several people to the Monty Hall problem - always a great party trick. And again, almost everyone instantly arrives at 50/50, and are as adamant that this is the correct solution as the next guy. So I decided to finally write the code to do it, but made two stipulations: 1) the code must mirror the way the problem is told as closely as possible. This will not be the most efficient code to write or the fastest to execute, but will hopefully be easy for readers to see through, so to speak. And 2) rather than just playing the game many times, I will let a population of individuals play it and compete with each other for a chance to reproduce (aka evolution). For full disclosure, the code is included below.
The Monty Hall code
The evolutionary dynamics
The objective of the organisms is to come up with the best strategy for playing the Monty Hall game. Each organism has just one “gene”, called MH01, and this gene determines the probability that when playing the game the organism chooses to stay or to switch. The value of MH01 is a number between 0 and 1. If the number is 0, the organism never switches door, and if it is 1, then the organism always switches, and if the value is, say, 0.4825, then there is a 48.25 percent chance that the organism switches door. Easy-peasy.
We do two experiments: 1) comparing two strategies (50% switching vs. 50% staying, or MH01=0 vs. MH01 = 1) without mutations, and 2) starting all individuals with MH01=0 and adding mutations to all offspring.
We start with a population of N=100 individual organisms. One organism is chosen at random among the N individuals to play the game. If it wins it gets to reproduce. In that case a copy of it now replaces one of the N organisms chosen at random (including its parent). Nothing happens if they lose the game. This results in a constant population size and overlapping generations. When an offspring replaces a hapless individual, the MH01 gene can mutate (in experiment 2). This results in MH01 increasing or decreasing by a small uniformly random value. And that’s it.
The evolved solution
Figure 2: Average population value of MH01 with large-effect mutations. Starting with 100% stayers (MH0=0). MH01 increases relatively fast, reaching the largest value after around 30,000 plays. The effect of mutations is uniformly distributed on the interval ±0.05 centered on the current value. Population size is N=100. The black lines are minimum (bottom) and maximum (top) values of MH01 in the population.
Figure 3: Average population value of MH01 with small-effect mutations. Starting with 100% stayers (MH0=0). MH01 increases relatively slowly, reaching the largest value after around 250,000 plays. The effect of mutations is uniformly distributed on the interval ±0.01 centered on the current value. Population size is N=100. The black lines are minimum (bottom) and maximum (top) values of MH01 in the population. There is less variation in MH01 in this case because the effect of mutations is lower than in the runs shown in figure 2.
Discussion
What a relief! When running simulations like this there is always the risk that for some unseen reason the evolved solution is different from what you anticipated. Thankfully that is not the case here: evolution favors the fittest organisms, and the fittest organisms are those that tend to switch when they play the game. Success!
Why does MH01 not go to fixation? In other words, why does the average population value of MH01 (blue lines) not become 1? The answer is that there is a mutational load (Wikipedia) caused by the effect of mutations. Offspring of a parent with MH01=1 has a 50% chance of having a lower value of MH01, so there will always be some individuals with a suboptimal value of MH01. What is increased in evolutionary dynamics is not fitness but free fitness. Free fitness is the sum of the logarithm of fitness and an entropy term that is non-zero when there is either mutation and/or drift. The term was introduced by Yoh Iwasa in 1988: Free fitness that always increases in evolution.
Let me reiterate that the answer of 2/3 chance to get the car when switching relies on the game host knowing where the car is, and deliberately opening a door that the contestant has not chosen and where there is a goat behind. If the host opens another door at random and there happens to be a goat behind it, then the probability of getting the car is only 50% for switching (and for staying).
You can play the Monty Hall game here, where you can also play the version where the host does not know which door has the car.
Answer in Genesis affirms evolution, sort of
Answer is Genesis (i.e., Ken Ham and the Creation Museum) has published a really nice description of the bedbug paper that came out earlier this year. The story is in short that bedbugs used to be one species feeding on bat blood, but now they are in the process of splitting into two species, with one specializing on humans. This has been going on for quite a while, but evolution is - mostly - a slow process, so have a little patience, yeah?
In Bedbugs, Scientists See a Model of Evolution, New York Times, by Carl Zimmer
In Bedbugs, Scientists Don't See a Model of Evolution, AiG, Dr. Elizabeth Mitchell
Dr. Mitchell (she's an obstetrician, by the way) writes that
But you know, she has a book:
In Bedbugs, Scientists See a Model of Evolution, New York Times, by Carl Zimmer
In Bedbugs, Scientists Don't See a Model of Evolution, AiG, Dr. Elizabeth Mitchell
Dr. Mitchell (she's an obstetrician, by the way) writes that
Genetic analysis supports the hypothesis that today’s common bedbug originated in bat-caves and, having transitioned to cave-dwelling people, then developed populations with a preference for people and people’s houses.That's what I call evolution, rather than development. But she won't go that far:
The bedbug does provide a living laboratory to study speciation—which is limited to variation within a created kind—but it does not provide a laboratory to show how new, more complex forms of living things evolve as Darwin poetically and imaginatively asserted.Here's her great description of natural selection
About 90% of the bedbugs infesting homes today are resistant to pyrethroid insecticides. However, any reports of rapidly “evolving resistance” are poorly worded. Bedbugs remain bedbugs. They don’t evolve into anything. Those genetically equipped to survive the assault of pesticides have restored their populations with pesticide resistant offspring. This is an example of natural selection (and possibly other mechanisms), as pesticide-resistant individuals selectively survive to breed another day.But why is this not evolution, then?
There is nothing in this research either reminiscent or predictive of the evolution of increasingly complex “new forms” either wonderful or dreadful. Instead, what this research demonstrates is that bedbugs are still bedbugs, varying within their created kind to survive and thrive in a sin-cursed world.Hold on! She just described how the human variety has evolved resistance to pesticides, so what gives? Note that the scientific jargon is that development is how an organism changes in its lifetime, while evolution is how the population changes over the generations. Pesticide resistance is not something that an individual bedbug first doesn't have, then experiences pesticide, and the develops resistance. No, either an individual has it from birth through genetics or not, just as Mitchell so eloquently describes the process. So pesticide resistance is exactly a new feature, an increase in information about the environment = an increase in complexity, through evolution by natural selection. I can only conclude that Mitchell both understands evolution and believes that it occurs.
But you know, she has a book:
But as we infer from Genesis 1 and observe in biology, living things—including bedbugs—only reproduce and vary within their created kinds. Bedbug research actually affirms this scriptural truth rather than lending any support to the bacteria-to-bedbug fallacies of Darwinian evolution.So with semantic tricks this is not evolution because it is development, and because, even though she agrees that this is an example of speciation, it is only variation within a created kind. This kind is not defined here, and I have never seen a rigorous, scientific definition (though I've seen one based on the Bible), so it remains a question of semantics that this is not evolution. But I am happy that she agrees that speciation occurs. \o/
CoE #78 is up
A very short edition of Carnival of Evolution is up today. A new blogger is hiding behind a pseudonym, David Hume, with two excellent posts on molecular evolution. That's the good news. The bad news is that I had to find almost all of the blog-posts myself, which means there were very few submissions by others, and clearly a lack of interest. :(
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