Applied Regression Analysis

A Second Course in Business and Economic Statistics

Terry Dielman

450 pages, parution le 20/09/2004

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Résumé

Applied Regression Analysis focuses on the application of regression to real data and examples while employing commercial statistical and spreadsheet software. Designed for both business/economics undergraduates and MBAs, this text provides all of the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and Discriminant Analysis. While only a prior introductory statistics course is required, a review of all necessary basic statistics is provided in chapter 2. The text emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets.

L'auteur - Terry Dielman

Terry Dielman is professor of Decision Sciences at Texas Christian University. Terry received his Ph.D. at the University of Michigan (Business Statistics), his M.S. at the University of Cincinnati (Mathematics) and his B.A. at Emporia State University (Mathematics). His recent research focuses on Regression Analysis, Time Series Forecasting, Robust Statistical Procedures and the Analysis of Pooled Cross-Sectional and Time Series Data. His recent publications include “Bootstrap versus Traditional Hypothesis Testing Procedures for Coefficients in Least Absolute Value Regression” in the JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. He participates in the Editorial Board of the Journal of Business and Management, and consults for Forecasting Seminars and for various law firms.

Sommaire

An Introduction to Regression Analysis
Review of Basic Statistical Concepts
Simple Regression Analysis
Multiple Regression Analysis
Fitting Curves to Data
Assessing the Assumptions of the Regression Model
Using Indicator and Interaction Variables
Variable Selection
An Introduction to Analysis of Variance
Qualitative Dependent Variables: An Introduction to Discriminant Analysis and Logistic Regression
Forecasting Methods for Time-Series Data

A: Summation Notation
B: Statistical Tables
C: A Brief Introduction to MINITAB, Microsoft Excel, and SAS
D: Matrices and their Application to Regression Analysis
E: Solutions to Selected Odd-Numbered Exercises

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Thomson
Auteur(s)	Terry Dielman
Parution	20/09/2004
Nb. de pages	450
Format	19 x 24
Couverture	Relié
Poids	950g
Intérieur	Noir et Blanc
EAN13	9780534465483
ISBN13	978-0-534-46548-3