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Autore: | Nayebi Hooshang |
Titolo: | Advanced Statistics for Testing Assumed Causal Relationships : Multiple Regression Analysis Path Analysis Logistic Regression Analysis / / by Hooshang Nayebi |
Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Edizione: | 1st ed. 2020. |
Descrizione fisica: | 1 online resource (XII, 113 p. 125 illus., 101 illus. in color.) |
Disciplina: | 519.535 |
Soggetto topico: | Statistics |
Mathematics | |
Social sciences | |
Applied mathematics | |
Engineering mathematics | |
Applied Statistics | |
Mathematics in the Humanities and Social Sciences | |
Applications of Mathematics | |
Statistical Theory and Methods | |
Nota di contenuto: | 1. Multiple Regression Analysis -- 2. Path Analysis -- 3. Logistic Regression Analysis. |
Sommario/riassunto: | 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. |
Titolo autorizzato: | Advanced Statistics for Testing Assumed Causal Relationships |
ISBN: | 3-030-54754-X |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910483508403321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |