Paramètres
- 272pages
- 10 heures de lecture
En savoir plus sur le livre
This book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach. The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable. Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe
Achat du livre
Applying Regression and Correlation, Jeremy Miles, Mark Shevlin
- Langue
- Année de publication
- 2000
- product-detail.submit-box.info.binding
- (souple)
Modes de paiement
Il manque plus que ton avis ici.
- Titre
- Applying Regression and Correlation
- Sous-titre
- A Guide for Students and Researchers
- Langue
- Anglais
- Auteurs
- Jeremy Miles, Mark Shevlin
- Éditeur
- SAGE Publications Ltd
- Publié
- 2000
- Format
- souple
- Pages
- 272
- ISBN10
- 0761962301
- ISBN13
- 9780761962304
- Séries
- Mots clés
- Nonfiction, Sciences sociales, Science et Mathématiques, Psychologie, Mathématiques, Sociologie, Recherche, Statistiques
- Évaluation
- 4,6 sur 5
- Description
- This book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach. The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysis and can be extended to deal with first one, and then more than one independent variable. Extending the model from the mean to a regression analysis provides a powerful, but simple, way of thinking about what students believe


