Regression Analysis (350-0-20)
Instructors
Arvind Krishna
Meeting Info
University Hall 102: Mon, Wed 2:00PM - 3:20PM
Overview of class
This is the Undergraduate level section of the 350 course. (note, Ad Hoc MS in Applied Statistics students may register for this section)
This is a regression course with a combination of theory and application. We will discuss statistical estimation and inferential techniques such as least-squares, confidence intervals, and hypothesis tests, regarding both the regression parameters and the error variance. We will also discuss some important theoretical results and derivations. We will study the regression models by specifying what the underlying assumptions are, how to check them through diagnostics, and how to build models based on data. Homework will be assigned weekly or biweekly (about 6 assignments). There will be a midterm exam, a final exam, a course project, and in-class quizzes.
Registration Requirements
Prerequisite or co requisite: STAT 320-1
Learning Objectives
By the end of the class students are expected to (1) formulate statistical questions for a real life problem; (2) use visualization techniques to explore the data; (3) choose the appropriate statistical methods and justify the choice; (4) perform regression analysis using R programming; (5) describe and present the data analysis results; (6) understand and derive relevant theoretical results related to regression.
Evaluation Method
Homework assignments (30%), midterm exam (20%), final exam (25%), in-class quizzes (5%), and final project (20%).
Class Materials (Required)
The Elements of Statistical Learning, 2nd edition, https://hastie.su.domains/ElemStatLearn/ , by Trevor Hastie, Robert Tibshirani, and Jerome Friedman, ISBN: 978-0387848570
Applied Linear Statistical Models, 5th or 4th edition by J.Neter et al. ISBN‐10:007310874 XISBN‐13:978‐0‐07‐310874‐2 Publisher: McGraw‐Hill/Irwin Year:2004. Amazon price as in May 2022 is about $69 (paper back , pb2013) to $136. Northwestern bookstore should have the textbook available for purchase.
Class Materials (Suggested)
Lecture notes and R codes will be posted on canvas.
Class Notes
Computing: Statistical Software, R will be used to demonstrate the methodologies. Template R programs will be posted on the course web page.
Class Attributes
Formal Studies Distro Area
Enrollment Requirements
Enrollment Requirements: Prerequisite STAT 202-0 or STAT 210-0 or STAT 232-0 or PSYCH 201 or IEMS 201 or IEMS 303.
Co-requisite: STAT 320-1 or STAT 383-0 or MATH 310-1 or MATH 311-1 or MATH 314-0 or MATH 385-0 or ELEC_ENG 302-0 or IEMS 202-0