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Applied regression analysis : [Book] : a second course in business and economic statistics / Terry E. Dielman.

By: Contributor(s): Material type: TextTextSeries: Duxbury applied seriesPublication details: Belmont, CA : Brooks/Cole Thomson Learning, c2005.Edition: Fourth editionDescription: 1 v. (various pagings) : illustrations ; 25 cm. + 1 CD-ROM (4 3/4 in.)ISBN:
  • 053446548X (hardback)
Subject(s): DDC classification:
  • 330.01519536 22
LOC classification:
  • HB137 .D54 2005
Other classification:
  • 330.01519536
Summary: 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.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books Books Junaid Zaidi Library, COMSATS University Islamabad 330.01519536 DIE-A (Browse shelf(Opens below)) Available 53889
Total holds: 0

Rev. ed. of: Applied regression analysis for business and economics. 3rd ed.

Accompanying CD-ROM contains data stored in various formats including Minitab, SAS, JMP, SPSS, Excel and ASCII.

Includes bibliographical references and index.

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.

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