Summer 2023 Decision, Risk & Operations Management B7114 section 002

Applied Regression Analysis

Applied Regression Analys

Call Number 12426
Points 1.5
Grading Mode Standard
Approvals Required None
Instructor David Juran
Method of Instruction In-Person
Course Description This course is designed for students who wish to increase their capability to build, use, and interpret statistical models for business.

A primary goal of the course is to enable students to build and evaluate statistical models for managerial use in finance, operations and marketing. The focus is on generating managerially useful information and practical decision-making tools, rather than on statistical theory per se. A number of actual business cases are studied.

Concepts covered are multiple linear regression models and the computer-assisted methods for building them, including stepwise regression and all subsets regression. Emphasis is placed on diagnostic and graphical methods for testing the validity and reliability of regression models.

Course topics include a review of basic statistical ideas, numerical and graphical methods for summarizing data, simple linear and nonlinear regression, multiple regression, qualitative independent and dependent variables, diagnostic methods for assessing the validity of statistical models. The course studies applications of regression to business forecasting and also examines alternative times series forecasting models, including exponential smoothing.

While the primary focus of the course is on regression models, some other statistical models will be studied as well, including cluster analysis, discriminant analysis, analysis of variance, and goodness-of-fit tests.

Term project: A major aspect of course is the opportunity to carry out a practical statistical analysis project of one’s own. Students work in teams on a problem of their own choosing. The goal of the project is to develop a useful statistical model for a specific business problem, with the professor providing ongoing guidance and advice during the course of project. The teams will give an oral presentation of their results at the term’s end.

Excel is used for basic statistical analysis as well as for developing straightforward regression models. In addition, more advanced commercial statistical software, such as Minitab or SAS, is used to carry out more complex and advanced analyses. In addition to the term project, there will be several computer-based assignments.
Web Site Vergil
Department Decision, Risk and Operations
Enrollment 16 students (50 max) as of 5:05PM Friday, April 12, 2024
Subject Decision, Risk & Operations Management
Number B7114
Section 002
Division School of Business
Open To Business, Journalism
Campus Morningside
Section key 20232DROM7114B002