Table of Contents

Basic Experimental Design and Analysis: Introduction: What is Science? Modelling Reality; The Fundamental Role of Measurement in Science; Bacon's Legacy: Causal Models, and How to Test Them; How Hypothesis Testing Copes With Uncertainty: The Legacy of Karl Popper and Ronald Fisher; Basic Descriptive Statistics (And How Pierre Laplace Saved the World); Gaussian Distributions, the Fundamental Building Block of Statistics; Randomized Controlled Trials, the Model T Ford of Experimental Science; Simple One-Factor Analysis of Variance, Contrasts and Post Hoc Tests; Repeated Measures Designs, and Their ANOVA Counterparts; Multifactorial and Mixed Designs, and Their ANOVA Counterparts; Association Tests of Similar Variables: Correlation and the Chi-Square; Checking the Assumptions: Data Cleaning, Transforming Variables and the Non-Parametric Alternative; A Taxonomy of Experimental Designs: Introducing the X-O Diagram and Quasi-Experimental Studies; Why Should We Believe This? Varieties of Validity; Significance is Not Everything: Introducing Power; Planning and Writing Up a Project or Experiment; More Advanced Statistical Methods: When You Can Only Observe: The Natural Setting for Multiple Regression; More Advanced Regression: Mediation, Moderation and Suppression; Getting to the Essence of Things: Exploratory Factor Analysis; Basic Signal Detection Theory; Meta-Analysis, or How to Learn From Experience;