# Syllabus¶

## Instructor & TAs¶

• Professor:Jonathan Taylor
• Office: Sequoia Hall #137
• Phone: 723-9230,
• Email
• Office hours: T 1:00-3:00 or by appointment.
• TA: Yunjin Choi
• Office: Sequoia Hall 207
• Email
• Office hours: M 9:00-11:00
• TA: Minyong Lee
• Office: Sequoia Hall 207
• Email
• Office hours: W 9:00-11:00
• TA: David Walsh
• Office: Sequoia Hall 207
• Email
• Office hours: Th 4:00-6:00
• Final exam: Following the Stanford calendar: Thursday, March 20 @ 3:30PM-6:30 PM, Mudd Chemistry Building LEC.

## Schedule & Location¶

TTh 11:00-12:15, BraunLec

## Computing environment¶

We will use R for most examples, with some python mixed in, particularly numpy and matplotlib.

All of the course notes are written with the ipython notebook, a great tool for interactive computing. Most R code is run through the R magic.

## Prerequisites¶

An introductory statistics course, such as STATS 60.

## Course description¶

By the end of the course, students should be able to:

• Enter tabular data using R.
• Plot data using R, to help in exploratory data analysis.
• Formulate regression models for the data, while understanding some of the limitations and assumptions implicit in using these models.
• Fit models using R and interpret the output.
• Test for associations in a given model.
• Use diagnostic plots and tests to assess the adequacy of a particular model.
• Find confidence intervals for the effects of different explanatory variables in the model.
• Use some basic model selection procedures, as found in R, to find a best model in a class of models.
• Fit simple ANOVA models in R, treating them as special cases of multiple regression models.
• Fit simple logistic and Poisson regression models.

## Evaluation¶

For those taking 4 units:

• 5 assignments (50%)
• data analysis project (20%)
• final exam (30%) (according to Stanford calendar: Th 03/20 @ 3:30PM)

For those taking 3 units:

• 5 assignments (70%)
• final exam (30%) (according to Stanford calendar: Th 03/20 @ 3:30PM)

### Project¶

The data analysis project description describes what is needed for your project. It is due March 14, 2014.

### Practice exam¶

You can find a practice exam here. Here are practice solutions.

Here is a 2nd practice exam with solutions.