Every lecture below pulls its title, topic, and description straight from the .qmd file’s YAML frontmatter — nothing here is hand-typed. Ordering comes from the order: field, which the sync_order_from_folder_names.R pre-render hook fills in automatically from each folder’s WW_MM_ number prefix. To reorder or move a lecture to another week, just change the two leading numbers on its folder name — the frontmatter and this page update themselves on the next render.
| Lecture | Topic |
|---|---|
| Lecture: Getting Started | Asking a question, meeting R, and making your first graph |
| Lecture: Wrangling Your Data | Importing more than one way, reshaping columns, and saving what you make |
| Lecture: Describing Your Data | Mean, spread, counting correctly, and group summaries |
| Lecture: Graphing Effectively | Boxplots, axis limits, a reusable themes file, multi-panel figures, and saving publication-ready output |
| Lecture: Probability & Inference | From the normal curve to the confidence interval |
| Lecture: T-Tests: One, Two, Paired | Comparing means |
| Lecture: Non-Parametric T-Tests | Rank-based tests |
| Lecture: Power and Type I & II Error | Errors and power |
| Lecture: Study Design & Sampling | Designing studies |
| Lecture: Correlation vs Linear Models | Relationships |
| Lecture: Multiple Regression | Several predictors |
| Lecture: Analysis of Variance (ANOVA) | Single-factor ANOVA |
| Lecture: Two-Way ANOVA | Factorial designs |
| Lecture: Nested ANOVA | Hierarchical designs |
| Lecture: Linear Mixed Models | Random effects for nested and hierarchical data |
| Lecture: GLM & Logistic Regression | Generalized linear models |
| Lecture: ANCOVA — Analysis of Covariance | Covariates |
| Lecture: Multivariate Statistics | Multivariate intro |
| Lecture: Principal Component Analysis | Ordination |
| Lecture: NMDS & Cluster Analysis | Community ordination |
| Lecture: Review | Course review |
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