STA 221 - Regression Analysis: Theory and Applications

This page contains an outline of the topics, content, and assignments for the semester. Note that this schedule will be updated as the semester progresses, with all changes documented here.

week	dow	date	topic	prepare	slides	notes	ae	hw	lab	project	due
1	Th	Jan 9	Welcome to STA 221!
	F	Jan 10	Lab 00: Welcome + Getting started
2	Tu	Jan 14	Simple linear regression (SLR)
	Th	Jan 16	SLR: Model assessment
	F	Jan 17	Lab 01: Computing + linear algebra review
3	Tu	Jan 21	SLR: Matrix representation								Lab 01 due
	Th	Jan 23	Geometric interpretation
			Multiple linear regression
	F	Jan 24	Lab 02: Linear regression
4	Tu	Jan 28	MLR: Types of predictors								Lab 02 due
	Th	Jan 30	MLR: Types of predictors cont'd + Model comparison								HW 01 due, Statstics experience assigned
	F	Jan 31	Lab 03: Multiple linear regression + Meet your team!
5	Tu	Feb 4	Inference for regression								Lab 03 due
	Th	Feb 6	Inference for regression cont'd
	F	Feb 7	Lab: Project research topics
6	Tu	Feb 11	Inference for regression cont'd								Project topics due
	Th	Feb 13	Exam 01 review								HW 02 due
	F	Feb 14	Lab 04: Exam 01 review
7	Tu	Feb 18	Exam 01
	Th	Feb 20	No Lecture: Take-home exam
	F	Feb 21	Lab: Project proposal
8	Tu	Feb 25	MLR: Model conditions + diagnostics								Project propsal due
	Th	Feb 27	MLR: Multicollinearity
	F	Feb 28	Lab 05: Expanding multiple linear regression
9	Tu	Mar 4	MLR: Multicollinearity cont'd								Lab 05 due, Exam 01 corrections due, Team feedback due
			Variable transformations
	Th	Mar 6	MLR: variable transformation cont'd
	F	Mar 7	Lab: Project exploratory data analysis
10	Tu	Mar 11	No lecture: Spring break
	Th	Mar 13	No lecture: Spring break
	F	Mar 14	No lab: Spring break
11	Tu	Mar 18	Maximum likelihood estimation
	Th	Mar 20	Properties of estimators								HW 03 due, Project EDA due
	F	Mar 21	Lab 06: Maximum likelihood estimation
12	Tu	Mar 25	Probabilities + Odds + Odds ratios								Lab 06 due
	Th	Mar 27	Logistic regression (LR)
	F	Mar 28	Lab: Project presentations
13	Tu	Apr 1	LR: Prediction
	Th	Apr 3	LR: Model comparison
	F	Apr 4	Lab 07: Logistic regression
14	Tu	Apr 8	Logistic regression Inference								Lab 07 due, Team Feedback due
	Th	Apr 10	Logistic regression: Assumptions + Estimation								HW 04 due
	F	Apr 11	Lab: Project peer review
15	Tu	Apr 15	Exam 02 review
	Th	Apr 17	Exam 02
	F	Apr 18	Project work day
16	Tu	Apr 22	Project meetings								Statistics experience due
Exam period	Mo	Apr 28									Written report due
	We	Apr 30									Project highlights, Repo organzation due
	Th	May 1									Project survey due