**This is an introductory course in statistical data analysis**

The course aims to prepare researchers to intelligently apply basic statistical methods for the purposes of empirical analysis. However, to become effective users of statistics, students must learn elementary statistical concepts and theory, and be aware of the various assumptions of the methodology. The course will consequently combine simple exposition to statistical theory with practical use of statistical modeling. The course will alternate between lectures and practical lab sessions where students are encouraged to apply the material while learning to program in the statistical software R.

### What is this?

Lecture: Why study quantitative analysis?

R Notes: Getting started with R

R Script: Demonstration in R

### How Do I Learn about my data?

Lecture: Quantification and Measurement

Lecture: Descriptive Statistics

R Notes: Learn how to carry out operations in R

R Notes: Learn how to describe your data in R

### How do I learn about the things I can't observe?

Lecture: Inference

### How do I get from A to B?

Lecture: Relationships

Lecture: Regression

R Notes: Learn how to study associations in R

### Aren't we missing c?

Lecture: Multiple Regression

R Notes: Learn to do multiple regression in R

R Script: Multiple Regression

### What can go wrong and how do I fix it?

Lecture: Regression Warnings

### What Else can I do?

Lecture: Interaction effects