STAT-UB 3 Regression and Forecasting Model

Term: Fall 2021
Instructor: Dr. Lucius Riccio
Level: Undergraduate

Topics

Simple (one-predictor) linear regression, including the model assumptions, estimation, hypothesis tests, predictions, and prediction intervals;

Multiple regression, including the model assumptions, estimation, hypothesis tests, predictions, prediction intervals, variable selection, model building, residual analysis, and the checking of assumptions;

Description

The purpose of this course is to introduce the fundamentals of regression analysis by examining the nature and utility of data in business situations. Objectives include the methods of linear regression and multiple linear regression with emphasis on assessing statistical inference, as well as explanatory and predictive capabilities. The material in this course builds upon the use of methods learned in your first Stats class such as the control of statistical bias, data presentation, appreciation of probability and randomness, random variables, and statistical inference.