Master inferential statistics: estimation, point and interval estimation, hypothesis testing, null and alternative hypotheses, significance levels, Type I and Type II errors, and statistical power.
Comprehensive guide to the major non-parametric statistical tests—chi-square, median test, Mann-Whitney U, sign test, and Wilcoxon matched-pairs signed-ranks test—with formulas, applications, and worked examples.
Comprehensive guide to One-Way ANOVA: the F-ratio, between/within group variance, assumptions, worked examples with post-hoc t-tests, and applications in psychology research.
Understand the distinction between parameters and statistics, explore sampling error vs standard error, and learn the t-ratio distribution in psychological research.
A comprehensive introduction to parametric and non-parametric statistics—their definitions, key differences, and when each approach is appropriate in psychological research.
Comprehensive guide to the major parametric statistical tests—t-tests for two samples, ANOVA for three or more samples, and Pearson's r and Fisher's Z for correlation—including formulas, assumptions, and worked examples.