schedule.Rmd
Week | Date | Lecture topic | Lab topic | Notes | |
---|---|---|---|---|---|
1 | W | Aug. 16 | Course introduction | ||
F | Aug. 18 | Introduction to statistics | |||
2 | M | Aug. 21 | Introduction to linear models | Introduction to R | |
W | Aug. 23 | Introduction to linear models | |||
F | Aug. 25 | Principles of statistical inference | |||
3 | M | Aug. 28 | Principles of statistical inference | Introduction to RMarkdown | |
W | Aug. 30 | Linear models for simple categorical predictors (aka t-test) | |||
F | Sep. 1 | Linear models for simple categorical predictors (aka t-test) | |||
4 | M | Sep. 4 | Labor Day | No lab | |
W | Sep. 6 | Linear models for simple categorical predictors (aka t-test) | |||
F | Sep. 8 | Null hypothesis testing | |||
5 | M | Sep. 11 | Null hypothesis testing | t-tests* | |
W | Sep. 13 | Power | |||
F | Sep. 15 | Paper discussion: null hypothesis testing | Johnson 1999 | ||
6 | M | Sep. 18 | Linear models for categorical predictor w/ >2 levels (aka ANOVA) | ANOVA* | |
W | Sep. 20 | Linear models for categorical predictor w/ >2 levels (aka ANOVA) | |||
F | Sep. 22 | Multiple comparisons | |||
7 | M | Sep. 25 | Exam 1 review | Multiple regression | Exam 1 distributed |
W | Sep. 27 | Multiple regression | |||
F | Sep. 29 | Multiple regression | |||
8 | M | Oct. 2 | Interactions | Interactions* | Exam 1 due |
W | Oct. 4 | Interactions | |||
F | Oct. 6 | Evaluating assumptions | |||
9 | M | Oct. 9 | Evaluating assumptions | Evaluating assumptions* | |
W | Oct. 11 | Model selection | |||
F | Oct. 13 | Paper discussion: model selection | Tredennick et al. 2021 | ||
10 | M | Oct. 16 | Random effects | Model selection* | |
W | Oct. 18 | Nested designs | |||
F | Oct. 20 | Exam 2 review | Exam 2 distributed | ||
11 | M | Oct. 23 | Split-plot designs | Nested designs | |
W | Oct. 25 | Split-plot designs | |||
F | Oct. 27 | Fall break | Exam 2 due | ||
12 | M | Oct. 30 | Repeated measures | Split-plot designs* | |
W | Nov. 1 | Repeated measures | |||
F | Nov. 3 | Paper discussion: Pseudoreplication | |||
13 | M | Nov. 6 | Generalized linear models | Repeated measures* | |
W | Nov. 8 | GLM: Logistic regression | |||
F | Nov. 10 | GLM: Logistic regression | |||
14 | M | Nov. 13 | GLM: Poisson regression | Logistic regression* | |
W | Nov. 15 | GLM: Poisson regression | |||
F | Nov. 17 | Buffer | |||
15 | M | Nov. 20 | Thanksgiving break | Poisson regression* | |
W | Nov. 22 | ||||
F | Nov. 24 | ||||
16 | M | Nov. 27 | GLM: Zero-inflated data | TBD* | |
W | Nov. 29 | GLM: Zero-inflated data | |||
F | Dec. 1 | Exam 3 review | Exam 3 distributed | ||
17 | M | Dec. 4 | TBD | No lab |
* = Graded assignment