What actually is a p-value for? And what is a significant result? This book answers such questions by providing a compact introduction to inferential statistics. Our major focus is on the logic of inferential statistics and hypothesis testing: We cover the logic behind statistical tests, we then walk through the most common procedures (t-test, analysis of variance with and without repeated measures, correlation/regression) and discuss pitfalls of data analysis. The book thus helps developing a solid understanding of how common test procedures work, and how to interpret their results correctly. Hands-on examples from everyday research - including exemplary calculations with the programs SPSS and R - supplement each chapter. In addition to classical methods, we briefly discuss recent developments in psychological research methods.
This book is a translation of the original German 3rd edition of "Inferenzstatistik Verstehen" by Markus Janczyk and Roland Pfister. It is based on an AI-powered machine translation (by the service DeepL.com), with thorough follow-up editing by both authors.
Auflage
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Illustrationen
18
40 s/w Abbildungen, 18 farbige Abbildungen
XVII, 201 p. 58 illus., 18 illus. in color. With online files/update.
Maße
Höhe: 240 mm
Breite: 168 mm
Dicke: 13 mm
Gewicht
ISBN-13
978-3-662-66785-9 (9783662667859)
DOI
10.1007/978-3-662-66786-6
Schweitzer Klassifikation
Markus Janczyk studied psychology at the Universities of Halle-Wittenberg and Reno (USA), obtained his doctorate at the TU Dortmund University and habilitated at the Julius-Maximilians-University of Würzburg. He is currently a professor at the University of Bremen, where he heads the Research Methods and Cognitive Psychology Group. In his research, he is primarily interested in action control, multitasking, memory, and cognitive modeling.
Roland Pfister studied psychology at the Julius-Maximilians-University of Würzburg, where he wrote his doctoral thesis on the cognitive mechanisms of conscious rule breaking. In addition, he works on basic mechanisms of action control, the interplay of perception and action, and the history of psychology.
Introduction and descriptive statistics.- Basics of inferential statistics 1: random variables.- Basics of inferential statistics 2: population and parameter estimation.- Hypothesis testing and significance.- Difference hypotheses with a maximum of two groups: t-tests. Confidence intervals.- Error types, effect size and power.- Single factor analysis of variance.- Multifactorial analysis of variance.- Analysis of variance with repeated measures.- Correlation hypotheses: Correlation and regression.- Concluding remarks.
