June 10, 2020

Learn and visualize how melt reshapes dataframes from long to wide

May 17, 2020

Learn and visualize how pd.pivot_table reshapes data from long to wide form

May 14, 2020

Learn and visualize how pd.melt reshapes data from wide to long form

April 11, 2020

Use directed acyclic graphs and structural equation modeling to understand Lord's paradox.

Oct. 20, 2019

The only tutorial and cheatsheet you'll need to understand how Python numpy reshapes and stacks multidimensional arrays

Oct. 1, 2019

Deriving the derivative of the sigmoid function for neural networks

Sept. 15, 2019

Resources for making R packages

Sept. 7, 2019

Why is it bad to use z-scores to detect outliers and why you should use median absolute deviation instead

Aug. 7, 2019

Resources for learning principal components analysis and dimension reduction

Aug. 1, 2019

A list of online classes I've completed or am planning to take

July 24, 2019

What happens when you force the intercept to be 0 in a regression model and why you should (generally) never do it

July 6, 2019

A short tutorial on how to interpreting regression coefficients, including interaction coefficients.

April 13, 2019

A gentle, step-by-step intro to logistic regression, inverse logit and logit functions, and maximum likelihood estimation in the context of logistic regression

April 11, 2019

Resources for the amazing R data.table package

April 9, 2019

A gentle and intuitive introduction to Markov Chain Monte Carlo sampling with rejection sampling.

March 16, 2019

Step-by-step instructions describing how I deployed my ShinyApp with Docker and hosted it on a web server with DigitalOcean (using Mac OS X).

Feb. 22, 2019

Why are barplots or dynamite plots so bad? Comparing four different types of plots: barplot, boxplot, violinplot, and geom_quasirandom plot

Feb. 18, 2019

What is complete pooling, no-pooling, and partial pooling, and how to use data.table for no-pooling models (fit the same model, but separately to each group)

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Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/hauselin/rtutorialsite, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".