Chapter 1 Why statistics?

Part 1 Descriptive statistics

Chapter 2 Some basics: Variability and measurement

Chapter 3 Describing variables: Tables and diagrams

Chapter 4 Describing variables numerically: Averages, variation and spread

Chapter 5 Shapes of distributions of scores

Chapter 6 Standard deviation and z-scores: Standard unit of measurement in statistics

Chapter 7 Relationships between two or more variables: Diagrams and tables

Chapter 8 Correlation coefficients: Pearson’s correlation and Spearman’s rho

Chapter 9 Regression: Prediction with precision

Part 2 Significance testing

Chapter 10 Samples from populations

Chapter 11 Statistical significance for the correlation coefficient: A practical introduction to statistical inference

Chapter 12 Standard error: Standard deviation of the means of samples

Chapter 13 Related t-test: Comparing two samples of related/correlated/paired scores

Chapter 14 Unrelated t-test: Comparing two samples of unrelated/uncorrelated/

independent scores

Chapter 15 What you need to write about your statistical analysis

Chapter 16 Confidence intervals

Chapter 17 Effect size in statistical analysis: Do my findings matter?

Chapter 18 Chi-square: Differences between samples of frequency data

Chapter 19 Probability

Chapter 20 One-tailed versus two-tailed significance testing

Chapter 21 Ranking tests: Nonparametric statistics

Part 3 Introduction to analysis of variance

Chapter 22 Variance ratio test: F-ratio to compare two variances

Chapter 23 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA

Chapter 24 ANOVA for correlated scores or repeated measures

Chapter 25 Two-way or factorial ANOVA for unrelated/uncorrelated scores:

Two studies for the price of one?

Chapter 26 Multiple comparisons with in ANOVA: A priori and post hoc tests

Chapter 27 Mixed-design ANOVA: Related and unrelated variables together

Chapter 28 Analysis of covariance (ANCOVA): Controlling for additional variables

Chapter 29 Multivariate analysis of variance (MANOVA)

Chapter 30 Discriminant (function) analysis – especially in MANOVA

Chapter 31 Statistics and analysis of experiments

Part 4 More advanced correlational statistics

Chapter 32 Partial correlation: Spurious correlation, third or confounding variables,

suppressor variables

Chapter 33 Factor analysis: Simplifying complex data

Chapter 34 Multiple regression and multiple correlation

Chapter 35 Path analysis

Part 5 Assorted advanced techniques

Chapter 36 Meta-analysis: Combining and exploring statistical findings

from previous research

Chapter 37 Reliability in scales and measurement: Consistency and agreement

Chapter 38 Influence of moderator variables on relationships between two variables

Chapter 39 Statistical power analysis: Getting the sample size right

Part 6 Advanced qualitative or nominal techniques

Chapter 40 Log-linear methods: Analysis of complex contingency tables

Chapter 41 Multinomial logistic regression: Distinguishing between several

different categories or groups

Chapter 42 Binomial logistic regression

Chapter 43 Data mining and big data