## S631: Applied Linear Models I

### Class Description

Basic linear model theories. Simple linear regression and multiple linear regression: least square estimation, inference, ANOVA, Model selection and multicollinearity.

### Class Information

**School/Department: **Statistics

**Semester(s): **Fall

**Year(s) Offered: **_2018

**Class time: **
Tuesday, Thursday : 9:30A - 10:45A

**Instructor: **Arturo Valdivia - artvaldi@indiana.edu

### Other Details

**Sequence: ** Stat 632: Applied Linear Models II

**Prerequisites: ** Requires permission of instructor

**Algebra Required?: ** For proofs and homework.

**Calculus Required?: ** For derivations and homework.

**Recommended follow-up classes: ** Most other graduate level statistics courses.

**Substantive Orientation: ** Most units on campus including Statistics, Social Sciences, Biological Sciences, Informatics, Education.

**Applied/Theoretical: ** In the middle of theoretical/applied.

**Formal Computing Lab?: ** No

**Software Used: **
R

**How the software is used: ** computation, programming and data analysis

**Problem Sets: ** Yes, proofs and derivations

**Data Analysis: ** Yes

**Presentations: ** No

**Exams: ** Yes