Understanding Inferential Statistics

Comprehensible introduction to logic and classical methods of inferential statistics With evaluation examples for SPSS and R from everyday research Formal writing styles and aspects for advanced students in separate consolidation boxes

Autorentext

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.

Inhalt
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.