This is a side issue, but I wonder what changes could be made to the teaching of statistics, most importantly "stats for scientists" taught in college and even high school. What occurs to me right off the bat is that I learned stats by the use of formulas to boil data sets down to answers. For example, null hypothesis significance testing and the dreaded p-value. We had to do it this way, as widespread availability of computers was still on the horizon.
Today, computation is easy and cheap. I wonder if we could learn stats in a different way, perhaps starting by just playing with data, and simulated random numbers, graphing, and so forth. Can something like null hypothesis testing be taught primarily through bootstrapping, with the formulas introduced as an aside?
Yes I know that statistics is a formal branch of math, with theorems and proofs. I took that class. But the students who take "stats for scientists" don't ever see that side of it. Understanding the formulas without seeing the proofs is like trying to learn freshman physics without calculus.
That is essentially how Allen Downey approaches statistical education: the analytical solutions came first because we lacked the computational power. Now that we have cheap computation, we should exploit that to develop better intuition. His Bayesian book[0] is available as Jupyter notebooks.
That's pretty cool. I actually would like to see K-12 math education use more computation and data, with less of a focus on algebra (expression manipulation). This would be more reflective of how regular people, including STEM people, use math outside of school.
This is an interesting thread of thought. I personally find many concepts in statistics much easier to understand through a resampling/bootstrapping lens, and I plan to try it on my children once they're old enough.
Today, computation is easy and cheap. I wonder if we could learn stats in a different way, perhaps starting by just playing with data, and simulated random numbers, graphing, and so forth. Can something like null hypothesis testing be taught primarily through bootstrapping, with the formulas introduced as an aside?
Yes I know that statistics is a formal branch of math, with theorems and proofs. I took that class. But the students who take "stats for scientists" don't ever see that side of it. Understanding the formulas without seeing the proofs is like trying to learn freshman physics without calculus.