Bull! I have written programs and designed spreadsheets that perform massively complex analysis and it takes no more than about 20 minutes to teach people how use them, and these were business people. All they had to know is what data belonged where and few simple rules for data integrity testing. It is nothing but minor league math. I've written programs for engineers and it made no difference whether they knew the math or not as long as I did. They too required very minimal training to use the software. Using that software does not make anyone more or less competent in mathematics. Exponential decay and growth functions can be looked in up in a math textbook. That's no big deal.
The "probabilistic flaw" is only an artifact resulting from the assumption that the "endpoint" was the intended goal of evolution all along.
Wrong again! No such assumption was necessary. The endpoint is what it is, no different than calculating the number of dice rolls to get a 7, 8, 9 or any other number I want to test as an endpoint. There is no goal, just a result and how long it might take to get it.
If you are testing a particular endpoint, how is that not a goal? "No goal" would be calculating the number of dice rolls necessary to get "a" number, not "this" number.
You must be an amazing teacher, then, to be able to teach people in 20 minutes material that usually takes people a semester or longer to master. It used to take longer than that for our department statistician to explain to people how she wanted their data formatted for input into SPSS... if they wanted to learn how to input the data themselves, analyze it, format outputs in a meaningful fashion, and understand what those outputs actually meant, she would spend HOURS with them. And they would typically call her back with more questions, because they never could quite grasp everything she was trying to teach in one session.
You can teach a monkey to input numbers. Teaching people how to differentiate between whether they should choose a one-tail or a two-tail test, whether ANOVA or Student's t-test is more appropriate, what the difference is between paired and unpaired samples, how to recognize a normal vs. skewed distribution and what the skewing signifies, how to look at the output and assess whether the appropriate statistical test was applied in the first place, what a P-value is and why it tells us whether to accept or reject the hypothesis all takes a bit longer than 20 minutes, in my experience. I guess me and my statistician friend just aren't talented teachers like you.
Likewise, while you may be able to look up basic exponential and logarithmic functions in a textbook, I can guarantee that if you're generating data that is specific to the unique system that you have chosen to study, you won't find the correct logarithmic or exponential function needed to analyze the data within any textbook. You have to derive it yourself.
Wrong again! No such assumption was necessary. The endpoint is what it is, no different than calculating the number of dice rolls to get a 7, 8, 9 or any other number I want to test as an endpoint. There is no goal, just a result and how long it might take to get it.
No, the literal creationist unspoken assumption is that h. sapiens is a pre-determined endpoint, and they work backward from that to "determine" that the odds of h. sapiens resulting from the totally random process of evolution operating over billions of years is impossible. The reality is that evolution doesn't have goals, and h. sapiens is only one of a nearly infinite number of possible species that can result from evolution. The probability that evolutionary processes result in viable species is 1.