Schedule (subject to change)
FANR 6750: Experimental Methods in Forestry and Natural Resources Research
Fall 2025
schedule.Rmd| Week | Date | Lecture topic | Reading | Lab Topic | |
|---|---|---|---|---|---|
| 1 | W | Aug. 13 | Course introduction | Syllabus | |
| F | Aug. 15 | Introduction to statistics | Quinn chp. 1 | ||
| 2 | M | Aug. 18 | Introduction to linear models | Fieberg chp. 1.2-1.4 | Introduction to R |
| W | Aug. 20 | Introduction to linear models | |||
| F | Aug. 22 | Principles of statistical inference | Feiberg chp. 1.6-1.8 | ||
| 3 | M | Aug. 25 | Principles of statistical inference | Introduction to RMarkdown | |
| W | Aug. 27 | Principles of experimental design | Quinn chp. 7.1-7.2 | ||
| F | Aug. 29 | Principles of experimental design | |||
| 4 | M | Sep. 1 | Labor Day | No lab | |
| W | Sep. 3 | Linear models for simple categorical predictors (aka t-test) | Fieberg chp. 3.6 | ||
| F | Sep. 5 | Linear models for simple categorical predictors (aka t-test) | |||
| 5 | M | Sep. 8 | Null hypothesis testing | Fieberg chp. 1.10 | Sampling error* |
| W | Sep. 10 | Null hypothesis testing | |||
| F | Sep. 12 | Troubleshooting R workshop | |||
| 6 | M | Sep. 15 | Power | Quinn chp. 7.3 | t-tests* |
| W | Sep. 17 | Linear models for categorical predictor w/ >2 levels (aka ANOVA) | Fieberg chp. 3.7 | ||
| F | Sep. 19 | Linear models for categorical predictor w/ >2 levels (aka ANOVA) | |||
| 7 | M | Sep. 22 | Multiple comparisons | Fieberg chp. 3.9, 3.12 | ANOVA |
| W | Sep. 24 | Special topic: p-hacking | Fraser et al. 2018 | ||
| F | Sep. 26 | Exam 1 | |||
| 8 | M | Sep. 29 | Multiple regression | Fieberg chp. 3.2-3.5 | Multiple regression* |
| W | Oct. 1 | Multiple regression | |||
| F | Oct. 3 | Interactions | Fieberg chp. 3.8 | ||
| 9 | M | Oct. 6 | Interactions | Interactions* | |
| W | Oct. 8 | Evaluating assumptions | |||
| F | Oct. 10 | Model selection | |||
| 10 | M | Oct. 13 | Random effects | Evaluating assumptions* | |
| W | Oct. 15 | Nested designs | |||
| F | Oct. 17 | Split-plot designs | |||
| 11 | M | Oct. 20 | Split-plot designs | Nested design | |
| W | Oct. 22 | Special topic: AI | Bergstrom & West 2025 | ||
| F | Oct. 24 | Exam 2 | |||
| 12 | M | Oct. 27 | Repeated measures | Split-plot designs* | |
| W | Oct. 29 | Repeated measures | |||
| F | Oct. 31 | Fall break | |||
| 13 | M | Nov. 3 | Repeated measures | Repeated measures* | |
| W | Nov. 5 | Buffer | |||
| F | Nov. 7 | Generalized linear models | |||
| 14 | M | Nov. 10 | GLM: Logistic regression | Model selection* | |
| W | Nov. 12 | GLM: Logistic regression | |||
| F | Nov. 14 | GLM: Poisson regression | |||
| 15 | M | Nov. 17 | GLM: Poisson regression | GLMs* | |
| W | Nov. 19 | GLM: Zero-inflated data | |||
| F | Nov. 21 | GLM: Zero-inflated data | |||
| 16 | M | Nov. 24 | Special topic: Causal inference | Fieberg chp. 7 | No lab |
| W | Nov. 26 | Thanksgiving break | |||
| F | Nov. 28 | ||||
| 17 | M | Dec. 1 | Exam 3 | No lab |
* = Graded assignment