Looking to extend your understanding of statistical methods and data analysis skills? This text shows you how to apply advanced statistical models to data across the behavioural and social sciences.
This approachable book explains how to develop, estimate, and test statistical models with demonstrations using R. It gives you a strong grounding in key techniques such as multiple regression, multilevel modelling, factor analysis, and structural equation modelling, and helps you move beyond rigid statistical tests to confidently choose an appropriate model for reaching strong conclusions from your data.
This second edition includes:
Accompanied by datasets and R code for you to practice techniques at your own pace, this book is an accessible guide for anyone looking to advance their statistical understanding.
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David B. Flora is a Professor in the Department of Psychology at York University in Toronto, Canada. Dr. Flora has also served as Coordinator of the Quantitative Methods Area in York’s graduate program in psychology as Coordinator of York’s Statistical Consulting Service. As a quantitative psychologist, Dr. Flora is a coauthor on numerous journal articles focused on quantitative methodology itself as well as on a wide range of articles in which advanced quantitative methods are applied to substantive research topics in psychology. Dr. Flora earned his PhD from the Quantitative Psychology program at the University of North Carolina at Chapel Hill. Although he is now a Canadian, Dr. Flora remains a Tar Heel born and a Tar Heel bred.
Advance your statistical analysis skills with this accessible guide, which demonstrates how to apply a model-based approach to your own data and research.
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Paperback. Zustand: New. Looking to extend your understanding of statistical methods and data analysis skills? This text shows you how to apply advanced statistical models to data across the behavioural and social sciences.This approachable book explains how to develop, estimate, and test statistical models with demonstrations using R. It gives you a strong grounding in key techniques such as multiple regression, multilevel modelling, factor analysis, and structural equation modelling, and helps you move beyond rigid statistical tests to confidently choose an appropriate model for reaching strong conclusions from your data.This second edition includes:Two new chapters on logistic regression and missing data.Updated and improved content on causal models, mediation and modelling change over time with longitudinal data.Examples of real-world research from psychology, sociology, business and management, education, and more. Accompanied by datasets and R code for you to practice techniques at your own pace, this book is an accessible guide for anyone looking to advance their statistical understanding. Artikel-Nr. LU-9781529622614
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