STA305: Design and Analysis of Experiments MOC

This map indexes every atomic note for STA305, organized along the logical flow of experimental design and hypothesis testing.

Experimental Design Basics

Core design ideas: randomized experiments, observational studies, and blocking-based control.

Hypothesis Testing Foundations

Core ideas for hypothesis tests: t-tests, randomization distributions, and p-values.

Power and Sample Size

Power, sample-size planning, and related comparison methods.

Causal Inference

Foundations of causal inference: potential outcomes, SUTVA, and propensity scores.

Diagnostic Plots and Assumptions

Diagnostic plots and tools for checking assumptions.

One-Way ANOVA

One-way analysis of variance and related building blocks.

ANOVA Assumptions and Alternatives

ANOVA assumptions, diagnostics, and effect size.

Power Analysis for ANOVA

Power analysis and sample-size planning for ANOVA.

Multiple Comparisons

Multiple comparisons and FWER control.

Factorial Designs

Factorial designs with two or more factors and interaction analysis.

Factorial Design Effects and Interactions

Main effects and interactions in factorial designs.

Factor Coding

Coding schemes for categorical factors.

Regression

Linear regression models.

Reference Materials


Last updated: 2026-04-01