Advanced Statistics for Testing Assumed Causal Relationships: Multiple Regression Analysis Path Analysis Logistic Regression Analysis

Author:   Hooshang Nayebi
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
ISBN:  

9783030547530


Pages:   113
Publication Date:   16 August 2020
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Advanced Statistics for Testing Assumed Causal Relationships: Multiple Regression Analysis Path Analysis Logistic Regression Analysis


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Overview

This book concentrates on linear regression, path analysis and logistic regressions, the most used statistical techniques for the test of causal relationships. Its emphasis is on the conceptions and applications of the techniques by using simple examples without requesting any mathematical knowledge. It shows multiple regression analysis accurately reconstructs the causal relationships between phenomena. So, it can be used to test the hypotheses about causal relationships between variables. It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable. It is an advanced statistical text for the graduate students in social and behavior sciences. It also serves as a reference for professionals and researchers.

Full Product Details

Author:   Hooshang Nayebi
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Weight:   0.454kg
ISBN:  

9783030547530


ISBN 10:   3030547531
Pages:   113
Publication Date:   16 August 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1.  Multiple Regression Analysis.- 2. Path Analysis.- 3. Logistic Regression Analysis.

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