The Dunning-Kruger Effect is Autocorrelation

 https://economicsfromthetopdown.com/2022/04/08/the-dunning-kruger-effect-is-autocorrelation

The Dunning-Kruger Effect shows up in all data sets, even when it shouldn't. Because it's deeply flawed statistics. 

Causal Inference for The Brave and True

 https://matheusfacure.github.io/python-causality-handbook/landing-page.html

from correlation to causation

The Guinness Brewer Who Revolutionized Statistics

 https://priceonomics.com/the-guinness-brewer-who-revolutionized-statistics/

I'd never heard of Gosset

An Introduction to Simpson’s Paradox

https://towardsdatascience.com/simpsons-paradox-d2f4d8f08d42
Why averages can be deceiving.

Statistical Modeling with Python: How-to & Top Libraries

https://medium.com/kitepython/statistical-modeling-with-python-how-to-top-libraries-44f6c8cc7ece
The usual suspects and a couple of others. 

These Are the Best Books for Learning Modern Statistics—and They’re All Free

https://getpocket.com/explore/item/these-are-the-best-books-for-learning-modern-statistics-and-they-re-all-free
 Got some heavy books here.

The Black-Scholes formula, explained

https://medium.com/cantors-paradise/the-black-scholes-formula-explained-9e05b7865d8a
The formula that makes all options possible. 

The Gambler Who Cracked the Horse-Racing Code

https://www.bloomberg.com/news/features/2018-05-03/the-gambler-who-cracked-the-horse-racing-code
$1B from horseracing?

The Complete Guide to Time Series Analysis and Forecasting

https://towardsdatascience.com/the-complete-guide-to-time-series-analysis-and-forecasting-70d476bfe775
correlation and seasonality, etc. 

Understanding Random Forest

https://towardsdatascience.com/understanding-random-forest-58381e0602d2
interesting machine learning algorithm, but very compute-intensive.

Basic Statistics Every Data Scientist Should Know

https://medium.com/better-programming/statistics-review-for-data-scientists-and-management-df8f94760221
a list of basic statistics concepts. 

Launching Today: Free Wolfram Engine for Developers

https://blog.stephenwolfram.com/2019/05/launching-today-free-wolfram-engine-for-developers/
And a ML world all to itself: the wolfram language. Now with a free developer version.

Statisticians want to abandon science’s standard measure of ‘significance’

https://www.sciencenews.org/article/statisticians-standard-measure-significance-p-values
Is this just a reaction against "p hacking"? What should the new standard be?

The 5 Basic Statistics Concepts Data Scientists Need to Know

https://towardsdatascience.com/the-5-basic-statistics-concepts-data-scientists-need-to-know-2c96740377ae
Not quite the Statistics 101 we grew up with, but for modern times.

basic probability

https://seeing-theory.brown.edu/basic-probability/index.html#section1
Really stunning visualizations about basic probability theory

You're all calculating churn rates wrong

https://catchjs.com/Blog/Churn
Yeah, but selling the C-suite on esoteric stats and long tail is a hard row to hoe.

The Extent and Consequences of P-Hacking in Science

https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002106
Excellent journal article about statistical fudging in scientific papers. 

A Gentle Introduction to Maximum Likelihood Estimation

https://towardsdatascience.com/a-gentle-introduction-to-maximum-likelihood-estimation-9fbff27ea12f
Translation: how to find the best parameters for my model. In Python.

Every story in the world has one of the six basic plots

http://www.bbc.com/culture/story/20180525-every-story-in-the-world-has-one-of-these-six-basic-plots
Vonnegut's vindicated via the use of R

The 10 Statistical Techniques Data Scientists Need to Master

https://towardsdatascience.com/the-10-statistical-techniques-data-scientists-need-to-master-1ef6dbd531f7
Overview of statistics for data science. Some I'm not familiar with.