The fundamentals should be strong like an oak tree
- Kernel Density Estimation
- Intuitive Guide to Understanding KL Divergence
- What are, why use and how to get marginal means
- Understanding Bayes: Visualization of the Bayes Factor
- Two-way ANOVA - the basics | interaction | two-way vs one-way
- Contrast coding in R
- Bayes’ Theorem Intuition
- Exploratory Factor Analysis
- A Practical Introduction to Factor Analysis: Exploratory Factor Analysis
- Custom R Regression Functions You Might Find Useful
- Rules of thumb on magnitudes of effect sizes
- Decomposing, Probing, and Plotting Interactions in R
- Plot One Variable: Frequency Graph, Density Distribution and More
- Analysis, Plotting, & Statistics Script
- Common statistical tests are linear models (or: how to teach stats)
- tmap : the easy way to plot thematic maps and show them interactively in R
- Why testing positive for a disease may not mean you are sick. Visualization of the Bayes Theorem and Conditional Probability
- Comparing Multiple Means in R
- ESMS Case 7 Robust methods for dealing with outliers
- Computation of Effect Sizes
- Work with models
- Data Wrangling in R
- R Tutorial: Linear mixed-effects models part 1- Repeated measures ANOVA
- Choosing the Correct Statistical Test in SAS, Stata, SPSS and R