Tutorial series

R for Statistics

6 tutorials — follow in order for the best learning path.

1. Descriptive Statistics in R: Mean, Median, and Spread

   Descriptive statistics in R using base functions and tidyverse: calculate mean, median, variance, standard deviation, and quartiles step by step.

   10 min read · beginner
2. Hypothesis Testing in R

   Learn how to perform hypothesis tests in R including t-tests, chi-square tests, and ANOVA. Covers p-values, significance levels, and interpreting results.

   15 min read · intermediate
3. Linear Regression in R

   Learn simple and multiple linear regression in R with lm(), including diagnostics, interpretation, predictions and visualization.

   15 min read · intermediate
4. Logistic Regression in R

   Learn how to build, interpret, and evaluate logistic regression models in R using the glm() function. Covers odds ratios, predictions, and model diagnostics.

   15 min read · intermediate
5. ANOVA in R, Learn how to perform Analysis of Variance (ANOVA)

   Learn how to perform Analysis of Variance (ANOVA) in R, including one-way ANOVA, two-way ANOVA, and post-hoc tests with practical examples.

   15 min read · intermediate
6. Regression Models in R: lm(), glm(), and Diagnostics

   Learn to fit, interpret, and diagnose linear and generalized linear regression models in R using lm() and glm().

   intermediate