Buch, Englisch, 245 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 400 g
Reihe: Use R!
Buch, Englisch, 245 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 400 g
Reihe: Use R!
ISBN: 978-1-4614-1237-3
Verlag: Springer
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely-used statistical methods in behavioral research, using a set of notes and annotated examples. The book will also help beginners learn more about statistics and behavioral research. These are statistical techniques used by psychologists who do research on human subjects, but of course they are also relevant to researchers in others fields that do similar kinds of research.
The authors emphasize practical data analytic skills so that they can be quickly incorporated into readers’ own research.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Entscheidungstheorie, Sozialwahltheorie
- Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
Weitere Infos & Material
Introduction.- Reading and Transformting Data Format.- Statistics for Comparing Means and Proportions.- R Graphics and Trellis Plots.- Analysis of Variance.- Linear and Logistic Regression.- Statistical Power and Sample Size Considerations.- Item Response Theory.- Imputation of Missing Data.- Linear Mixed Effects Models in Analyzing Repeated Measures Data.- Linear Mixed Effects Models in Cluster Randomized Studies.