Skip to main content

Ctrl+K

Course Overview

Syllabus
Schedule
Assignments (Github Classroom)
Topic List

Computing Resources

Git & Github Cheatsheet
Coding Cheatsheets
Common Formulas
Scientific Python Glossary

Week 1

Overview
- 01-06: Introduction & course logistics
- 01-08: What is statistics?
Lab
- 1. Configuring your computer for class
- 2. Introduction to Python & Computational Notebooks

Week 2

Overview
Lab
- Introduction to numpy
- Plotting with matplotlib

Week 3

Overview
Lab

Week 4

Overview
- 01-29 Relationships & Similarity
Lab

Week 5

Overview

Week 6

Overview

Week 7

Overview

Week 8

Overview

Week 9

Overview
- 03-04: Effect Size & Power Analysis
- 03-05: Transformations and Assumptions

Week 10

Overview

.md

03-12: Course Summary

Contents

What you can learn next

03-12: Course Summary#

What you can learn next#

previous

Linear Mixed Models II: LMMs with Categorical Predictors

Contents

What you can learn next

Please cite: Le, K., Jadhav, A. & Jolly, E. (2025). Statistical Intuitions for Social Scientists. DOI

© 2025 Eshin Jolly. This work is licensed under a Create Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0)