Learn how to calculate descriptive statistics in R, mean, median, mode, variance, standard deviation, quartiles, and more.
Tutorial series
R for Statistics
6 tutorials — follow in order for the best learning path.
- Descriptive Statistics in R
- 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.
- Linear Regression in R
Learn simple and multiple linear regression in R with lm(), including diagnostics, interpretation, predictions and visualization.
- 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.
- 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.
- Regression Models in R
Learn to fit, interpret, and diagnose linear and generalized linear regression models in R using lm() and glm().