Every activity below pulls its number, title, and topic straight from that file’s YAML frontmatter (see order: and subtitle: in each activity .qmd). Nothing on this page is hand-typed.
| Activity # | Activity | Topic |
|---|---|---|
| 1 | Measuring Leaves and Entering Data | Field observations, hypotheses, and organizing data |
| 2 | Meeting R | From the console to your first plot with the tree leaf data |
| 3 | Describing Our Data | Wrangling, descriptive statistics, and first visualizations |
| 4 | Worksheet 04 — Testing Our Hypothesis | The two-sample Welch’s t-test from assumptions to scientific report |
| 5 | Activity 4.5 — Build Your First Quarto Report | Turn your leaf analysis into a professional Word document |
| 6 | Worksheet 05 — Linear Regression | Building a calibration curve to predict leaf area from paper tracing mass |
| 7 | Worksheet 06 — Real Climate Data in R | Downloading, summarizing, and modeling Duluth weather station data |
| 8 | Your Final Project Starts Now | Finding real data, asking a real question, and building toward a real answer |
| 9 | Worksheet 07 — Wide, Long, and Wild: Pivoting Real Data | Reshaping Lake Superior ice cover with pivot_longer() and pivot_wider() |
| 10 | Worksheet 10 — Factors: Ordering and Cleaning Categorical Data | Reorder, rename, and lump penguin categories with forcats — for cleaner plots and models |
| 11 | Worksheet 11 — One-Way ANOVA with Palmer Penguins | Comparing three species, checking assumptions, and post-hoc tests with emmeans |
| 12 | Worksheet 12 — Joins: Combining Two Bigfoot Tables | Keys, mutating joins, and filtering joins to build a map-ready dataset |
| 13 | Worksheet 13 — Mapping Bigfoot Sightings | Turn latitude/longitude into maps with sf and geom_sf, then build a per-state choropleth |
| 14 | Lecture 14 | |
| 15 | Lecture 15 - Class Activity ANCOVA | |
| 16 | Lecture 16 - Class Activity MANOVA | |
| 17 | Lecture 17 - Class Activity PCA | |
| 18 | Lecture 18 - Class Activity: NMDS and PERMANOVA |
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