# Contents

“Sometimes you must trust that you have the ability to find the answers yourself” Milton

## Contents

### Chapter list

- Chapter 1: Why you need science
- Chapter 2: Reporting research, variables and measurement
- Chapter 3: Summarizing Data
- Chapter 4: Fitting models (central tendency)
- Chapter 5: Presenting data
- Chapter 6: z-scores
- Chapter 7: Probability
- Chapter 8: Inferential statistics
- Chapter 9: Robust estimation
- Chapter 10: Hypothesis testing
- Chapter 11: Modern approaches to theory testing
- Chapter 12: Assumptions
- Chapter 13: Relationships
- Chapter 14: The general linear model
- Chapter 15: comparing two means
- Chapter 16: Comparing several means
- Chapter 17: Factorial designs

### Alphabetic list of selected topics covered

ANOVA (including robust methods and Bayesian approaches), assumptions (additivity, homoskedasticity, linearity, independent errors, normality etc.), bar charts, Bayes factors, Bayesian methods, Bayes theorem, bias (sources and correcting for it), boxplots, central limit theorem, chi-square test, confidence intervals, correlation (including robust methods and Bayesian approaches), effect sizes, Fisher’s exact test, frequency distributions, histograms, IQR, likelihood ratio, mean, median, meta-analysis, mode, null hypothesis significance testing (including power, Type I and II errors, error rates, criticisms), probability theory (classical and empirical), range, regression (including robust methods and Bayesian approaches), robust estimation, sampling theory, sampling distributions, scatterplots, standard deviation, standard error, *t*-tests (including robust methods and Bayesian approaches), variance, *z*-scores.