Advanced Statistics for Testing Assumed Causal Relationships: Multiple Regression Analysis Path Analysis Logistic Regression Analysis: University of Tehran Science and Humanities Series
Autor Hooshang Nayebien Limba Engleză Paperback – 17 aug 2021
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Specificații
ISBN-13: 9783030547561
ISBN-10: 3030547566
Pagini: 113
Ilustrații: XII, 113 p. 125 illus., 101 illus. in color.
Dimensiuni: 178 x 254 mm
Greutate: 0.24 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria University of Tehran Science and Humanities Series
Locul publicării:Cham, Switzerland
ISBN-10: 3030547566
Pagini: 113
Ilustrații: XII, 113 p. 125 illus., 101 illus. in color.
Dimensiuni: 178 x 254 mm
Greutate: 0.24 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria University of Tehran Science and Humanities Series
Locul publicării:Cham, Switzerland
Cuprins
1. Multiple Regression Analysis.- 2. Path Analysis.- 3. Logistic Regression Analysis.
Textul de pe ultima copertă
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.
Caracteristici
Provides nontechnical descriptions that help the reader to learn quickly Includes twenty-one examples on test of the causal relationships that help the reader to understand applications well Presents innovative explanations of the various effects of variables, raw, direct, indirect, spurious, and pure