Regression and Forecasting Models for Business Applications
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Overview
Subject area
STA
Catalog Number
9000
Course Title
Regression and Forecasting Models for Business Applications
Department(s)
Description
This course provides a thorough review of regression and forecasting approaches as applied to business applications. Among the topics covered are residual and influence analysis; multiple regression models, including selection criteria, curvilinear regression, dummy variables, and logistic regression; and time series models, including the classical multiplicative model, moving averages, exponential smoothing, and the autoregressive model.
Typically Offered
Fall, Spring, Summer
Academic Career
Graduate
Liberal Arts
No
Credits
Minimum Units
3
Maximum Units
3
Academic Progress Units
3
Repeat For Credit
No
Components
Name
Lecture
Hours
3
Requisites
023422