Understanding Multivariate Research : A Primer For Beginning Social Scientists / / William Berry (Florida State University), Mitchell S. Sanders (Florida State University)

• Record Nr.: UNINA9910789759603321
• Autore: Berry William
• Pubbl/distr/stampa: London : , : Taylor and Francis, , 2018
• ISBN: 0-429-98299-2; 0-429-97191-5; 1-283-27657-7; 9786613276575; 0-8133-4628-2
• Edizione: [First edition.]
• Descrizione fisica: 1 online resource (105 p.)
• Disciplina: 300/.7/2
• Soggetti: Social sciences - Research - Methodology; Multivariate analysis; Regression analysis
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Contents; Tables and Figures; Preface for Teachers and Students; Acknowledgments; 1 Introduction; 2 The Bivariate Regression Model; 3 The Multivariate Regression Model; 4 Evaluating Regression Results; 5 Some Illustrations of Multiple Regression; 6 Advanced Topics; 7 Conclusion; Glossary; References; Index
• Sommario/riassunto: "Although nearly all major social science departments offer graduate students training in quantitative methods, the typical sequencing of topics generally delays training in regression analysis and other multivariate techniques until a student's second year. William Berry and Mitchell Sanders's Understanding Multivariate Research fills this gap with a concise introduction to regression analysis and other multivariate techniques. Their book is designed to give new graduate students a grasp of multivariate analysis sufficient to understand the basic elements of research relying on such analysis that they must read prior to their formal training in quantitative methods. Berry and Sanders effectively cover the techniques seen most commonly in social ; science journals--regression (including nonlinear and interactive models), logit, probit, and causal models/path analysis. The authors draw on illustrations from across the social sciences, including political science, sociology, marketing and higher education. All topics are developed without relying on the mathematical language of probability theory and statistical inference. Readers are assumed to have no background in descriptive or inferential statistics, and this makes the book highly accessible to students with no prior graduate course work."--Provided by publisher.