In this course, you will learn approaches to analyzing multivariate data sets, emphasizing the analysis of variance, linear regression, and logistic regression. You will learn techniques for checking the appropriateness of proposed models, such as residual analyses and case influence diagnostics, and techniques for selecting models. The class emphasizes data analysis over mathematical theory.

By the end of the semester, you will…

• Know methods for analyzing multivariate datasets and understand how these methods are applied in research
• Know how to check whether proposed statistical models are appropriate for given data
• Develop a proficiency in addressing complex research questions using statistical evidence
• Understand the process of data-based research by working on an independent research project

Course Information

Lectures

Location: Old Chem 116
Time: Tu/Th 3:05p - 4:20p

Labs

Location: Old Chem 101
Time: M 3:05p - 4:20p or M 4:40p - 5:55p

Teaching Team and Office Hours

	Name	Email	Office Hours
			Day & Time	Location
Instructor	Dr. Maria Tackett	maria.tackett@duke.edu	M 1p - 2:30p Th 10a - 11:30a	Old Chem 118B
Teaching Assistants
	Yuhan Chen	yuhan.chen@duke.edu	Tu 11a - 1p	Old Chem 203B
	Cathy Lee	pin.chian.lee@duke.edu	W 3p - 5p	Old Chem 203B
	Jose San Martin	jose.san.martin@duke.edu	Th 6:30p - 8:30p	Old Chem 203B

Course Materials

Textbook

The Statistical Sleuth: Third Edition by Ramsey and Schafer.

Computing

RStudio available through Duke VM-Manage personal Docker container.