Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences - Info and Reading Options
By Jacob Cohen, Leona S. Aiken, Patricia Cohen and Stephen G. West
"Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences" was published by Taylor & Francis Group in 2014 - New York London, it has 736 pages and the language of the book is English.
“Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences” Metadata:
- Title: ➤ Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
- Authors: Jacob CohenLeona S. AikenPatricia CohenStephen G. West
- Language: English
- Number of Pages: 736
- Publisher: Taylor & Francis Group
- Publish Date: 2014
- Publish Location: New York London
“Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences” Subjects and Themes:
- Subjects: ➤ Correlation (statistics) - Regression analysis - Correlation (Statistics) - Social sciences - Statistical methods - Regression Analysis - Analyse de régression - Corrélation (Statistique) - Sciences sociales - Méthodes statistiques - Correlation
Edition Identifiers:
- The Open Library ID: OL33467752M - OL25091971W
- ISBN-13: 9781138012387 - 9780203774441 - 9781134800940 - 9781134801015 - 9781134801084
- All ISBNs: 9781138012387 - 9780203774441 - 9781134800940 - 9781134801015 - 9781134801084
AI-generated Review of “Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences”:
"Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences" Description:
Open Data:
chapter 1. Introduction -- chapter 2. Bivariate correlation and regression -- chapter 3. Multiple regression/correlation with two or more independent variables -- chapter 4. Data visualization, exploration, and assumption checking : diagnosing and solving regression problems I -- chapter 5. Data-analytic strategies using multiple regression/correlation -- chapter 6. Quantitative scales, curvilinear relationships, and transformations -- chapter 7. Interactions among continuous variables -- chapter 8. Categorical or nominal independent variables -- chapter 9. Interactions with categorical variables -- chapter 10. Outliers and multicollinearity : diagnosing and solving regression problems II -- chapter 11. Missing data -- chapter 12. Multiple regression, correlation and causal models -- chapter 13. Alternative regression models : logistic, Poisson regression, and the generalized linear model -- chapter 14. Random coefficient regression and multilevel models -- chapter 15. Longitudinal regression methods -- chapter 16. Multiple dependent variables : set correlation
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