> I'm hoping to see, over time, a shift away from ad-hoc null hypothesis testing in favour of linear models (yes, in introductory courses, from the start-- see link below) and Bayesian-by-default approaches.
Is there anything where I can start today, as a guinea pig? My statistics education is basically zero.
It goes over Bayes' Theorem early on, which I assume is Bayesian-by-default. I didn't realize this isn't universal.
I watched it because my professor seemed to be teaching from the same textbook, so it followed the same general course structure. The textbook we used was "Probability and Statistics for Engineering and the Sciences — 9th edition". You can find a PDF of the eighth edition just by googling the name.
You could probably follow along just by taking notes during the video lectures, but if you want to give yourself homework, the textbook provides a lot of practice problems.
Bayes Theorem is universal. It’s one of the most fundamental results in probability.
Bayesian statistics is not. Most basic intro courses go the frequentist routes for historical reasons, but really both methods have their pros and cons.
There are other comments here that suggests a number of books at varying levels. "Introduction to Modern Statistics" is very approachable in its presentation.
Is there anything where I can start today, as a guinea pig? My statistics education is basically zero.