This book's use of real data in examples and exercises helps students gain practical insights into regression and forecasting concepts. It is intended for the regression analysis course for students of business and economics or as a second course in business statistics found in schools of business or in departments of statistics and economics. (Prerequisites: college algebra and introductory business statistics.) The author includes: -- Use of the computer as the primary method of analysis with a focus on the interpretation of regression output -- Integration of cross-sectional models with time-series models throughout -- A data disk containing relevant data from examples and exercises, formatted for major statistical packages -- Many exercises that require interpretation and build on previously learned concepts -- Instructions for both Minitab RM (Release 10 for Windows RM) and SAS in new Using the Computer sections in each chapter -- An introduction to discriminant analysis and logistic regression in Chapter 9 (Qualitative Dependent Variables) -- A separate chapter covering analysis of variance topics to allow flexibility of coverage -- Data sets with real data from journals and actual business settingsData on City Mileage for Automatic ( 1 ) and Manual (0) Transmission Cars TABLE 2 . ... 12.9 USAA Balanced 13.7 USAA Income Stock 11.6 Weitz Series Value 20.0 SOURCE: Kiplingera#39;s Mutual Funds 94 (AcKiplinger Washington Editors, Inc.). ... 0 Cadillac De Ville 16 Acura Vigor 20 0 Cadillac Eldorado 16 Alfa Romeo 1 64 17 0 Cadillac Fleetwood 16 Alfa Romeo Spider 22 0 Cadillac Seville aamp; STS 16anbsp;...
|Title||:||Applied Regression Analysis for Business and Economics|
|Author||:||Terry E. Dielman|
|Publisher||:||Duxbury Resource Center - 1996|