Syllabus –Math676 – Spring 2011
Data Analysis with R
Instructor: Dr. Dang Office hours: T Th 8:30-10:30 or by appoint.
Office: Hume 315 Phone: 662-915-7409
Class time: 1:00-2:15 pm Place: Hume Hall 331
Textbook: Data Analysis and Graphics Using R: An Example-based Approach, 3rd
Goals: This course provides an introduction to data-analysis based on the open source
R environment, which is a globally adopted tool for exploratory statistics and modeling.
During the course the students will explore different kinds of datasets using both
graphical and numerical approaches. The emphasis is on hands-on analysis, graphical
display, and interpretation of data. After the course students will handle the basic
concepts to do diverse data analysis using R.
Grade policy: Homework 50%
2 Projects 50%
Contents to be covered:
Brief introduction of R: Chapter 1 1.1-1.9, Chapter 14 14.1-14.7;
Exploratory data analysis: Chapter 2 2.1-2.3;
Introduction of statistical models and inference: Chapter 3 3.1-3.4, Chapter 4.1-4.8;
Linear regression: Chapter 5 5.1-5.5, Chapter 6 6.1-6.8;
Generalized linear models: Chapter 8 8.1-8.6;
Multi-level and repeated measure models: Chapter 10 10.1-10.7;
Tree-based methods: Chapter 11 11.1-11.8;
Multivariate data analysis: Chapter 12 12.1-12.3.
1. All work must be typed. For some, I may ask for submitting codes electronically
so that I can rerun.
2. Graphics should be of high quality, clear to convey information.
3. For projects, students should submit report with a clear explanation of methods,
interpretation of results and conclusions.