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Applied Linear Regression, Third Edition is thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, this Third Edition stresses using graphical methods to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results. This text is an excellent tool for learning how to use linear regression analysis techniques to solve and gain insight into real-life problems.
Achat du livre
Wiley Series in Probability and Mathematical Statistics: Applied Linear Regression, Sanford Weisberg
- Langue
- Année de publication
- 1980
Modes de paiement
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- Titre
- Wiley Series in Probability and Mathematical Statistics: Applied Linear Regression
- Langue
- Anglais
- Auteurs
- Sanford Weisberg
- Éditeur
- John Wiley & Sons
- Publié
- 1980
- Pages
- 283
- ISBN10
- 0471044199
- ISBN13
- 9780471044192
- Séries
- Mots clés
- Nonfiction, Manuels, Science et Mathématiques, Mathématiques
- Description
- Applied Linear Regression, Third Edition is thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, this Third Edition stresses using graphical methods to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results. This text is an excellent tool for learning how to use linear regression analysis techniques to solve and gain insight into real-life problems.