schedule.Rmd| Week | Date | Lecture topic | Lab topic | Notes | |
|---|---|---|---|---|---|
| 1 | W | Aug. 14 | Course introduction | ||
| F | Aug. 16 | Introduction to statistics | |||
| 2 | M | Aug. 19 | Introduction to linear models | Introduction to R | |
| W | Aug. 21 | Introduction to linear models | |||
| F | Aug. 23 | Principles of statistical inference | |||
| 3 | M | Aug. 26 | Principles of statistical inference | Introduction to RMarkdown | |
| W | Aug. 28 | Linear models for simple categorical predictors (aka t-test) | |||
| F | Aug. 30 | Linear models for simple categorical predictors (aka t-test) | |||
| 4 | M | Sep. 2 | Labor Day | No lab | |
| W | Sep. 4 | Linear models for simple categorical predictors (aka t-test) | |||
| F | Sep. 6 | Null hypothesis testing | |||
| 5 | M | Sep. 9 | Null hypothesis testing | t-tests* | |
| W | Sep. 11 | Power | |||
| F | Sep. 13 | Troubleshooting R workshop | Reading (TBD) | ||
| 6 | M | Sep. 16 | Linear models for categorical predictor w/ >2 levels (aka ANOVA) | ANOVA* | |
| W | Sep. 18 | Linear models for categorical predictor w/ >2 levels (aka ANOVA) | |||
| F | Sep. 20 | Paper discussion: null hypothesis testing | Johnson 1999 | ||
| 7 | M | Sep. 23 | Multiple comparisons | Multiple regression | |
| W | Sep. 25 | Exam 1 review | Exam 1 distributed | ||
| F | Sep. 27 | Multiple regression | |||
| 8 | M | Sep. 30 | Multiple regression | Interactions* | |
| W | Oct. 2 | Interactions | Exam 1 due | ||
| F | Oct. 4 | Interactions | |||
| 9 | M | Oct. 7 | Evaluating assumptions | Evaluating assumptions* | |
| W | Oct. 9 | Model selection | |||
| F | Oct. 11 | Paper discussion: model selection | Tredennick et al. 2021 | ||
| 10 | M | Oct. 14 | Random effects | Model selection* | |
| W | Oct. 16 | Exam 1 discussion | |||
| F | Oct. 18 | Nested designs | |||
| 11 | M | Oct. 21 | Split-plot designs | Nested designs | |
| W | Oct. 23 | Split-plot designs | |||
| F | Oct. 25 | Exam 2 review | Exam 2 distributed | ||
| 12 | M | Oct. 28 | Repeated measures | Split-plot designs* | |
| W | Oct. 30 | Repeated measures | |||
| F | Nov. 1 | Fall break | Exam 2 due | ||
| 13 | M | Nov. 4 | Repeated measures | Repeated measures | |
| W | Nov. 6 | Exam 2 review | |||
| F | Nov. 8 | Generalized linear models | |||
| 14 | M | Nov. 11 | GLM: Logistic regression | Logistic regression* | |
| W | Nov. 13 | GLM: Logistic regression | |||
| F | Nov. 15 | GLM: Poisson regression | |||
| 15 | M | Nov. 18 | GLM: Poisson regression | Poisson regression* | |
| W | Nov. 20 | GLM: Zero-inflated data | |||
| F | Nov. 22 | GLM: Zero-inflated data | |||
| 16 | M | Nov. 25 | Exam 3 review | No lab | |
| W | Nov. 27 | Thanksgiving break | |||
| F | Nov. 29 | Exam 3 distributed | |||
| 17 | M | Dec. 2 | TDB | No lab |
* = Graded assignment