Minireference blog

These past months, I’ve been running a Reading Group for the No Bullshit Guide to Statistics and this week we finally reached Section 3.4 that explains hypothesis testing procedures like the one-sample $t$-test.

I just finished working on a calculus tutorial that introduces key ideas like limits, derivatives, and integrals in a condensed manner.

After seven years in the works, I’m happy to report that the No Bullshit Guide to Statistics is finally done and available as a digital download from Gumroad: gum.co/noBSstats.

In another tab, I’m writing the announcement blog post for the No Bullshit Guide to Statistics.

I recently compiled a list of linear algebra textbook recommendations for people interested to learn more about linear algebra.

Learning statistics is greatly facilitated by using a computational platform for doing statistics calculations and visualizations.

If I’ve learned anything about the startup world, it is that you have to listen to your customers, which in my case are the readers of the No Bullshit Guide textbooks.

I was talking with friends recently about an interesting phenomenon that all self-taught programmers have observed, which we ended up calling “learning loops.”

Over the years several readers have suggested (sometimes demanded!)

Let’s talk about the problems with the teaching of statistics.