Introductory statistics
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TextSeries: Wiley series in probability and mathematical statisticsPublication details: New York: Wiley, 1990. Edition: 5th edDescription: xvi, 711 pages : illustrations (some color) ; 25 cmISBN: 0-471-61518-8 (hbk.)Subject(s): Mathematical statistics | Probabilities | Mathematical modelsDDC classification: 519.5 WON Summary: An updated and revised edition of the popular introduction to statistics for students of economics or business, suitable for a one- or two-semester course. Presents an approach that is generally available only in much more advanced texts, yet uses the simplest mathematics consistent with a sound presentation. This Fifth Edition includes a wealth of new problems and examples (many of them real-life problems drawn from the literature) to support the theoretical discussion. Emphasizes the regression model, including nonlinear and multiple regression. Topics covered include randomization to eliminate bias, exploratory data analysis, graphs, expected value in bidding, the bootstrap, path analysis, robust estimation, maximum likelihood estimation and Bayesian estimation and decisions
| Item type | Current library | Call number | Copy number | Status | Date due | Barcode |
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Book
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Teaching & Research Resource Centre - 1 - Economics, Mathematics and Statistics | 519.5 WON (Browse shelf(Opens below)) | 1 | Available | M-75723 |
Includes bibliographical references and Index
An updated and revised edition of the popular introduction to statistics for students of economics or business, suitable for a one- or two-semester course. Presents an approach that is generally available only in much more advanced texts, yet uses the simplest mathematics consistent with a sound presentation. This Fifth Edition includes a wealth of new problems and examples (many of them real-life problems drawn from the literature) to support the theoretical discussion. Emphasizes the regression model, including nonlinear and multiple regression. Topics covered include randomization to eliminate bias, exploratory data analysis, graphs, expected value in bidding, the bootstrap, path analysis, robust estimation, maximum likelihood estimation and Bayesian estimation and decisions
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