## Content

### What is this course about?

This is an introductory statistics course intended for undergraduate students. Topics include exploratory data analysis (graphs and simple summary statistics), inference using hypothesis tests and confidence intervals, simple linear regression, one-way ANOVA, and chi-squared tests for two- way tables. Emphasis will be placed on being able to use these tools with real data. Students are expected to be comfortable with computers as we will be using R on a regular basis.

“All models are wrong, but some are useful.”– George E. P. Box

### Prerequisites

**Interests in R and RStudio**All class assignments will be in R. If you need to remind yourself of R, or you're not very familiar with R, you can come to the R intro/review session in week 1 (listed in the schedule).

### Reference Texts

The following texts are useful, but none are required.

- Alan Agresti, Christine Franklin, and Bernhard Klingenberg. Statistics: The Art and Science of Learning from Data (4th Edition)
- Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. An Introduction to Statistical Learning with Applications in R
- George Casella and Roger L. Berger. Statistical Inference (2nd Edition)