**Instructor**

Feng Liang : liangf AT illinois DOT edu

Phone: (217) 333-6017

Office hour: Tuesday, noon-1pm or by appointment

Tue/Thur, 2:00-3:20PM, Lincoln Hall 1090

The first lecture is on Tuesday, January 19, 2016.

**Course Description**

The course covers the theory of linear models, analysis of variance with one-, two-, and higher-way layouts, random effects models and mixed models. Mathematical and interpretational aspects of the models will be covered along with the theory behind statistical estimates, confidence intervals and multiple hypothesis tests. There will be some (just some) data analysis, but data analysis is covered in greater depth in Stat 425.

Stat 424 requires familiarity with linear algebra and calculus based statistics at the level of Math 415 and Stat 410. Students are also expected to have taken a data analysis course and know how to use R at the level of Stat 425.

**Text**

- Lecture notes by Professor John Marden
- Plane Answers to Complex Questions, 4th Edition, by Ronald Christensen (Springer). You can download the whole E-book from our library.
- lme4: Mixed-effects Modeling with R [Download pdf] by Douglas M. Bates

**Teaching Assistant**

Yunbo Ouyang, youyang4 AT illinois DOT edu

TA Office hours: Mon/Wed, 3:00-4:00pm, 122 Illini Hall.

**Homework**

Homework must be turned in by 4:30p.m. to the STAT424 homework drop box (on the first floor of Illini Hall near the elevator) or online via Compass by the indicated due day. Please do NOT send your homework to the TA/Instructor by email attachment, unless you are asked to do so.

Some homework problems will require students to submit a copy of necessary R code on Compass.

Each question will be given a score of 0, 1, or 2 according to the following rules:

- A score of 0 will be given if either nothing was written, or if the grader could not determine how anything that was written related to any correct solution of the problem.
- A score of 1 will be given to solutions that are not perfect but show some reasonable progress towards a correct solution. The grader is allowed to determine what “reasonable” means for each problem.
- A score of 2 will be given to perfect solutions that are written legibly with all work leading to the solution provided.

There will be roughly 8 assignments. In each assignment, the problems for graduate students and undergraduate students may vary. **Late homework will not be accepted; no homework score will be dropped.**

You shall get 100% for your homework if you finish no less than 85% of the assignment: suppose the total homework score is 120 and yours is 100, then your final score (out of 100) for homework will be calculated as follows:

$$ 100 \times \min \left ( \frac{100}{120 \times 0.85}, 1 \right ) = 98.$$

You can discuss homework problems with other students but should write your solutions independently using your own words. Copying homework solutions from another student, from past Department solutions, or from online solutions is cheating and plagiarism, and is a violation of Academic Integrity.

**Exams**

- Midterm: 2:00-3:20PM, Tuesday, April 05
- Final: 7:00-9:30PM, Tuesday, May 10

Students who must miss a scheduled midterm or final examination for any reason (athletic, religious, personal, etc.) should if possible discuss the alternative arrangements with the instructor well ahead of time.

If you miss the midterm due to illness on the day of the exam, the exam will be counted as “excused”, meaning that the percentage of that exam (in computing the final grade) will be reallocated to the final exam, provided that you have necessary evidence as requested by the instructor.

If you choose to attend an exam while suffering from illness, that exam determines your score and you will not receive any special consideration.

**Grading**

- 50% Homework
- 20% Midterm
- 30% Final

The grading scale will be ROUGHLY as follows:

- 90 -100% A
- 80 – 90% B
- 70 – 80% C
- 60 – 70% D

**Computing**

Students are expected to know R.

- The official intro, “An Introduction to R“.
- “Introduction to R” (105-page PDF)
- “simpleR” (PDF) by John Verzani.
- “The R Inferno” (PDF) by Patrick Burns
- “R Fundamentals and Programming Techniques” (PDF) by Thomas Lumley
- The R Markdown Cheat Sheet (PDF)
- The ggplot2 Cheat Sheet (PDF)
- Some R tutorial videos
- R Class Notes: Introducing R
- Resources to help you learn and use R at UCLA