Kit Rancangan Percobaan

Plan an experiment before running it: CRD, randomised block, Latin square, 2^k factorial, fractional factorial, centre points, seeded run order in R and Python

Power analysis and sample size worksheet: t-tests, proportions, ANOVA, correlation, regression, simulation power, sensitivity table and justification sentence

Protocol – materials, controls, KaTeX stats

Preregistration of hypotheses, design, sampling plan and stopping rule, variables, analysis plan, exclusions and deviations log

Classic and Welch one-way ANOVA, ANOVA table by hand, Tukey HSD, Games-Howell, planned contrasts, eta squared with CI and omega squared

Two-way between-subjects ANOVA: main effects, interaction plot, simple effects with emmeans and statsmodels, type I/II/III sums of squares, partial eta squared

Within-subject designs: repeated-measures ANOVA, sphericity, Greenhouse-Geisser and Huynh-Feldt, Friedman, Holm post hoc, split-plot overview, when to switch to mixed models

Analysis of covariance: covariate adjustment, homogeneity of slopes, adjusted means by hand and with emmeans, ANCOVA vs change scores, Lord's paradox, reporting

Clustered and longitudinal data: random intercepts and slopes, ICC, REML vs ML, lme4 and statsmodels MixedLM side by side, df methods, singular fits, reporting

Checking assumptions per method family (t/ANOVA, regression, GLMs, chi-square, correlation, repeated measures and mixed models): diagnostics, R and Python code, judgement rules and remedies

Choosing, computing and reporting effect sizes (d, g, d_z vs d_av, eta and omega squared, r, V, OR, RR, R squared, f squared) with CIs, conversions and R/Python code

Complete statistical analysis report for a thesis results chapter or client: plain-language summary, methods, descriptives, main analyses, assumption checks, sensitivity, limitations, reproducibility appendix, reviewer checklist