Paramètres
- 736pages
- 26 heures de lecture
En savoir plus sur le livre
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.
Achat du livre
Introductory Statistics, Thomas H. Wonnacott, Ronald J. Wonnacott
- Langue
- Année de publication
- 1990
- product-detail.submit-box.info.binding
- (rigide)
Modes de paiement
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- Titre
- Introductory Statistics
- Sous-titre
- Fifth Edition
- Langue
- Anglais
- Éditeur
- Wiley
- Publié
- 1990
- Format
- rigide
- Pages
- 736
- ISBN10
- 0471615188
- ISBN13
- 9780471615187
- Séries
- Mots clés
- Nonfiction, Commerce, Affaires & Gestion, Science et Mathématiques, Économie, Mathématiques
- Évaluation
- 3,4 sur 5
- Description
- 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.