Discussion Do undergrads really understand statistical inferen | Data Scientology

Discussion Do undergrads really understand statistical inference?



I posted this on an econometrics subreddit, but I want to also ask the more general statistics community. I hope that's okay! Note, I'm not an instructor, but starting my Ph.D. soon it hopes of teaching econometrics!

For Students: When you took your first statistical inference course, did you REALLY understand statistical inference by end of the course?

And for professors: Did you think the average student truly understands statistical inference?

By "really" and "truly", I'm not talking about being able to robotically calculate statistics: t-stat, p-value, CI and knowing when to reject and fail to reject the null... the stuff that gets you an A+ in Stats 101 if you can repeat them on the test. I got an A+ in intro statistics because we had past finals/midterms and I just "memorized" how to do it on the exam. The exam was literally the same as a practice midterm just different numbers/scenarios.

I'm talking about the bigger picture of statistical inference. If you asked your average introductory statistics student (or even just the A+ students) the more philosophical and epistemological questions, would they be able to give a confident answer?

1. Describe the big picture of statistical inference, what is it, what is it trying to do?
2. What does it mean that the sample estimate has a distribution? What does it mean that estimator is a random variable itself? Why is this a problem?
3. What is a hypothesis test doing? Why are you undertaking it? Why do people do it? What information does it give you that you didn't know before? What does it mean that you're assuming something to be true? What does it mean about your assumption when you reject/fail-to-reject the null?
4. What does it mean that you do not know the parameter and can never truly know what it is? How does affect your ability to understand how some random process works?

In my experience, I feel like most students get lost in learning the methods of calculations, they neglect to appreciate the bigger picture. It's like a student getting an A+ in Calculus because they can apply all the derivative rules perfectly but somehow never really understood that a derivative is the rate of change.

Most of the stuff intro stats students are evaluated on are things a computer can do for them. They are neglected or not truly tested to understand the epistemological value of knowing how statistical inference works.

/r/statistics
https://redd.it/ri7nmv