PSYC 640: Graduate Statistics
This page contains an outline of the topics, content, and preparation for the semester. This schedule will be updated as the semester progresses, with all changes documented here.
Readings on the schedule will need to be completed prior to the course they are listed for. We will build on the concepts you read about in that specific class period, so it is important that you have read.
| Week | Date | Topic | Prepare | Due |
|---|---|---|---|---|
| 1 | 08-25 | Getting set up + R foundations | Install R/RStudio; Bring a laptop | |
| 2 | 09-01 | LABOR DAY | Chapter 1 & 2 - ST Chapter 2 - MSR |
Lab 1 - Intro to Data Workflow |
| 3 | 09-08 | Descriptives, Visualizations + Communication | Chapter 5 - LSR Chapter 1 & 3 - R4DS |
|
| 4 | 09-15 | Design, Sampling + Inference | Chapter 2 - IMS Chapter 3 - MSR Chapter 7 - ST |
|
| 5 | 09-22 | Correlation + Effect Sizes | Chapter 5.1 & 13 - ST Chapter 11 - LSR |
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| 6 | 09-29 | Comparing Groups | Chapter 9 & 10 - ST Chapter 13 - LSR |
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| 7 | 10-06 | Simple Linear Regression | Chapter 14.1.1 - 14.1.4 - ST Chapter 7.1 - 7.2.4 - IMS Chapter 8.1.1 & 8.1.2 - MSR |
|
| 8 | 10-13 | FALL BREAK | Work on your midterm project | |
| 9 | 10-20 | Variability & Model Fit | Chapter 5 & 14- ST Chapter 7.2.5 - IMS |
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| 10 | 10-27 | Multiple Regression I: Adding Predictors | Chapter 15.3 - 15.5 - LSR Chapter 8 - IMS |
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| 11 | 11-03 | Multiple Regression II: Categorical Predictors | Chapter 9 - IMS Chapter 8.3 |
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| 12 | 11-10 | Assumptions + Model Diagnostics | Chapter 7.3 - IMS Chapter 14.5 - ST Chapter 8.1.4 - MSR Chapter 15.8 - LSR |
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| 13 | 11-17 | Expanding Regression | Chapter 14.2 & 14.3 - ST | |
| 14 | 11-24 | Model Building + Comparison | Chapter 15.8 - 15.10 - LSR | |
| 15 | 12-01 | Making R Work for You | Chapter 17 & 18 - ST | |
| 16 | 12-08 | Wrapping Up + Workshop |
Introduction to Modern Statistics (2e) –> IMS
Learning Statistics with R –> LSR
R for Data Science (2e) –> R4DS
Modern Statistics with R (2e) –> MSR
Statistical Thinking –> ST
An Introduction to Statistical Learning (2e) –> ISL
Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond (3rd ed.) –> DA