Should we teach both evolution and religion in school?

This is part of the fish-to-mammals aficionados' compulsion. Many of these people are atheists and they think they have found the scientific justification for their beliefs. Instead, what they have done is given a grossly over-extrapolated view of evolution. Evolution should be taught in schools, naive children need to be prepared to understand how drug-resistance evolve and why cancer treatments fail. Instead, they are indoctrinated into this mythological belief system and have no real understanding of the physics and mathematics of evolution.

No, you dumb cluck. Not everybody, just the fish-to-mammals aficionados. Not everyone you dumb cluck. At least Taq was able to figure out that it takes 3e9 replications for each possible substitution to occur. And one or more of those substitutions can be beneficial. You can't even do that simple calculation. So fish evolving into mammals isn't your only delusion. What a surprise, a fish-to-mammals aficionado who has to be spoon-fed mathematics in order to learn the subject. Didn't your teacher teach you how to read? Things haven't changed much for you since your high school days. Your problem is that you have to be spoon-fed to learn anything. And you don't have the intellect to examine this instruction for its veracity. Your indoctrination has made you a zealot. You are the one with the beam in your eye, you don't understand introductory probability theory yet you judge my math is wrong. Even Straggler acknowledges that this math is correct for explaining the evolution of drug-resistance Message 1849: Straggler's problem is that he can't present any real, measurable, and repeatable example of evolution that doesn't obey this math. It didn't take me that long to figure out the physics and mathematics of evolution. The evidence is clear and repeatable on that subject. It served a purpose, I figured out how to write the conclusion for my next paper.

Small population? You need to do a better job with your homework:
How Many People Have Ever Lived on Earth?
99% of people that have ever lived have lived in the last 10,000 years. And instead of trying to figure out how each trait somehow evolved, you should try to do the accounting for the genetic differences between humans and chimpanzees in less than a million generations with much smaller populations. That's true! That doesn't leave you with very many replications for adaptive mutations before that period. You have just made my argument that there is no rational way that humans and chimpanzees evolved from a common ancestor. You simply don't have the population sizes necessary for these kinds of evolutionary transformations. Clearly, this is not nearly a large enough population for the transformation to occur due to selection. Perhaps you want to claim that humans and chimps simply drifted from a common ancestor. That's an awful lot of fixations by drift you need to account for. Do you care to show us the math for that?

That's essentially the same as your claim "But with population growth nearly all the people that have ever existed did so well after the mesolithic era." Why don't you do the math yourself? Count the number of mutations required for each trait and determine the number of replications necessary for all these mutations to accumulate on some lineage. The math really isn't that hard. If you are having trouble doing this more complex case, start with the computation of the number of replications necessary for just a single trait occurring such as the mutation for malaria resistance. Isn't it about time that you fish-to-mammals aficionados start quantifying DNA evolution yourselves? I don't accept common descent as you accept this notion, i.e., simple replicator in the primordial soup + time = Straggler. What I do accept as common descent as what can be measured. Here is a video of common descent and a phylogenetic tree that I do accept, from the Kishony experiment:
https://www.youtube.com/watch?v=plVk4NVIUh8&t=1s
At about 1:45 in the video, they draw in the phylogenetic tree from this DNA evolutionary process and the accumulation of the mutations necessary for adaptation. Each node where the adaptation mutation occurs is a colony of about a billion members.The flaw in your argument is that you think these phenotypic variations somehow must have evolved after humans first appeared on earth and that the only way that they could appear is by mutation. There have been more than enough replications of humans over time for there to be lots of diversity in the population gene pool. Some of those mutations are beneficial in some environments, others are detrimental, and others are neutral. Not everyone has a mutation that gives resistance to malaria, not everyone has the correct alleles for blue eyes, or for fair skin, lactase persistence or alcohol tolerance. The environment will select for particular traits, Darwin's finch example demonstrates that and the same principles are demonstrated with subpopulations of humans in different environments. Web sites such as ancestry.com demonstrate that DNA analysis can determine what subset of the ancestral population you descended from because of the unique genetic characteristics of those subsets. But why can't this be done with human and chimpanzee DNA? The answer is quite simple. There are far too many genetic differences between the two species and not nearly enough replications to do the accounting for these differences, especially when you look at how similar the DNA is within each member of the same species. Surely, since 99% of the human population lived in the last 10,000 years, you would have to expect that most of the evolutionary change occurred in the same time period. You have a major accounting problem with your notion of common descent. My mathematical microscope has more than one lens. I've shown you how the high magnification mathematical lens works for a single mutation. The math doesn't get better for your view as you go to a lower magnification.

You live in a very small frozen wasteland. Is this your way of claiming that you understand introductory probability theory? Because you certainly haven't demonstrated that. And just because you have been indoctrinated into the fish-to-mammals clique, do you really think you understand anything about evolution? If so, explain the mathematics of the Kishony evolutionary experiment. Have your distant cousins, the bananas taught you anything? So what did learn from your teachers that indoctrinated you that you are a distant cousin to bananas? Did they explain to you how drug-resistance evolves or why cancer treatments fail? You are making an incorrect assumption here. I did not start this debate because I wanted to teach the fish-to-mammals aficionados how evolution works. I started this debate because I had writer's block on how to write the conclusion for my next paper. The strategy worked perfectly and I actually learned a little more detail on the Markov chain models of DNA evolution. It's too bad you haven't learned anything from this discussion and if it makes you feel better to blame me, that's all right. Maybe my problem is that I'm only 6'4" and not 6'6".

So you think that everyone on the Internet is fish-to-mammals aficionados? You fish-to-mammals aficionados have a habit of making gross over-extrapolations from your very small frozen wastelands. We are still waiting for you to present one empirical example of DNA evolution that contradicts the math I've presented. You have failed at that. We know, those seeds fell on rocky ground. But the fish-to-mammals seeds, that found fertile soil in your mind. How about that verse "whatsoever a man soweth, that shall he also reap"? Did the fish-to-mammals aficionado teach you that math? Is that what bananas tell you, "we are distant cousins"? Do you speak bananaese? Or do you have to put what they say into Google Translate? And it is clear you have never taken a course in introductory probability theory. But bananas talk to you and tell you that they are distant relatives. You have an interesting way of continuing your education. Don't worry, I'm going to submit my next paper soon. And this discussion has done a lot of good for me, it enabled me to break my writer's block and write the conclusion for that paper. And people on this forum claim there are scientists who post on this forum that understand probability theory. Where are they? Since I have experience with teaching, I can tell you there are some poor students out there. Most of the time, the reason they are poor students is that they don't do their homework.

I've already done plenty of probability calculations and have gotten them peer-reviewed and published. Why are you afraid of calculating the probability of a malaria resistance mutation occurring? At some time, you fish-to-mammals aficionados need to start learning how to do the mathematics of evolution. Why don't you start right here? Taq has already given you a big hint. For a mutation rate of e-9, it takes 3e9 replications for each of the possible substitution mutations to occur at the given site. How much more of a hint do you need?

Why can't you use probability theory on evolution? After all, the mutation rate is simply the probability that an error on DNA replication will occur at the given site in a single replication. It is probability theory that sinks the TOE, in particular, the multiplication rule.

Only one so far, Taq. And it took a lot of discussions to get him to do the math for the number of replications necessary for every possible substitution mutations to occur at a given site. His calculation confirmed my math. And he fully understood the consequences this has for the TOE. That's why he started to talk about recombination. His problem is that I had already published a paper on the mathematics of recombination and shown that it has very little effect on DNA evolution. There have been none on this forum that demonstrate any understanding of the Markov chain models of DNA evolution. Only some moron who claims to understand the model but can't even tell us what the initial conditions for the model is. I'll try to be more diplomatic then telling them they are "blithering idiots and you are doing the math incorrectly", but no matter how I say this, it is going to be very upsetting to a lot of "fish-to-mammals" aficionados. After all, even if you don't understand the math, do you think that cherry-picking some gene from an entire genome, ignore the rest of the genome that you can get any kind of an accurate idea how closely related the two species are? That idea is so ludicrous that you could look for a gene in a banana that is similar to your gene and by that logic you are related. If the genes are exact matches, your parents are bananas by that logic.

The mathematics is complete, the paper is written, the only thing remaining is the last case study for the simulation of two drugs simultaneously for the Kishony experiment. That calculation on my computer system (an older I3 Intel chip running at about 1GHz) can only do 1.5 trillion replications/day. It will take about 200 trillion replications to get the one double beneficial mutation. Right now the calculation is at 60 trillion replications and I'm probably going to stop at 100 trillion replications because it is clear where the solution is converging and I don't think it's worth running the calculation for another 2-3 months. Solving Markov chain calculations can take huge amounts of computer time. All the other cases comparing the standard Jukes-Cantor model with the stationary transition matrix with the non-stationary transition matrix (with selection) are done. The non-stationary model accurately simulates the Kishony experiment. In addition, I've been invited by a good statistics journal that publishes papers on Markov chain models to submit a paper. It will probably happen by the end of summer. I assume the peer-review process will take some time because I expect there to be controversy surrounding this paper. What I don't expect is that there will be a problem with the math. I've published too many mathematical papers and when the math is correct and correlates correctly with the empirical evidence, everything seems to harmonize. And this is one of those cases.

You should do a little more research on the subject, canines and felines already do eat grass.
Why Do Dogs Eat Grass | VCA Animal Hospital
http://www.animalplanet.com/pets/why-do-cats-eat-grass/
DNA evolution is no different that any other type of stochastic process such as coin tossing, dice rolling, card drawing, etc. That's why when you do the math properly, you can predict the evolutionary process and do DNA identification. Do you doubt the validity of DNA identification because this is done based on the rules of probability theory. You have to play the hand your are dealt. The only real examples of evolution we have available which can be measured and repeated are experiments such as the Kishony and Lenski experiments. You can only say with certainty how genetics works right now. Why would you think that genetics worked differently in the past and will work differently in the future?

This calculation isn't that large. And I don't think these types of Markov chain calculations would benefit because each transition step must be done sequentially. These calculations are simple matrix multiplications. The one base problem is a 1x4 vector times a 4x4 matrix and the two base problem is a 1x16 vector times a 16x16 matrix for each transitional step. That ends up being 4 equations to evaluate for the 1 base Jukes-Cantor model and 16 equations for the 2 base Jukes-Cantor model. The Jukes-Cantor model has some symmetry that can be taken advantage of to reduce the 2 base case to just 4 equations but these 4 equations have to be evaluated before the system can take the next transition. All this math is simple additions and multiplications and requires very little computer memory, the rate of calculation is clock rate limited. There are some 5GHz computers available which could cut the computation time down to less than a month but I decided its not worth the money and effort. By time I got the faster computer and got the appropriate computer programs set up and running properly would take about a week and this would just be for this one task. The computers I have now work fine for all that I do. I actually wanted more time to think about this paper before I submit it anyway. You should be able to see why based on the response to these discussions. But thanks for your advice anyway. Once this calculation is complete, I don't think it will be necessary to go on to the three base Jukes-Cantor system. Actually, this paper already predicts that behavior (as well as the two base system):
The mathematics of random mutation and natural selection for multiple simultaneous selection pressures and the evolution of antimicrobial drug resistance

Dig a little deeper:
Get Your Paws on These Vegan Dog and Cat Food Products | PETA And you can't assume that things worked differently in the past unless you have some evidence to do so. With scientific analysis, you work with what you have available and you test your assumptions. So far, every experiment known validates probability theory. If you have experimental evidence which invalidates the theory, you should present it. Are you talking about abiogenesis or the TOE? Because both are shown to be mathematically irrational theories by probability theory. But if you think that things worked differently in the past, you need to present your evidence. If you honor the Bible, why don't you capitalize the word?

No, what I am saying is there is evidence today that carnivores can survive on non-meat diets. Where is your evidence from the past or future that says carnivores can only survive on meat? Why not, you do it all the time. You just did it with the diets of canines and felines. What evidence do you have that they can only survive on meat in the past or the future. We do have evidence that they can survive on a vegetarian diet today. Do you think there was a time when the multiplication rule of probabilities did not apply in a stochastic process?

Because that is how drug-resistant bacteria evolve and the reason cancer treatments fail. And the reason that combination therapy works for the treatment of hiv is the multiplication rule of probabilities.