Module Artifacts — 10 items
An outline of the module's topics, spanning ANOVA fundamentals, underlying assumptions, F-statistic logic, and one-way ANOVA, which instructors use to structure and preview the learning sequence for the week.
A comprehensive reading covering ANOVA concepts including its definition, assumptions, F-statistic derivation, and one-way ANOVA procedures, which learners study as the primary text reference for the module.
A landing page that consolidates all Module 14 instructional resources — including a PowerPoint, a recorded lecture, and a Google Colab notebook — giving learners a single access point for ANOVA materials.
Introduces ANOVA as a method for comparing means across three or more groups simultaneously, explaining why it is preferable to running multiple t-tests, and serves as a conceptual starting point before learners engage with the mechanics of the technique.
Details the key assumptions that must be met before applying ANOVA — such as normality, homogeneity of variance, and independence — helping learners and instructors verify that data are appropriate for the analysis before proceeding.
Explains the logic behind the F-statistic, showing how ANOVA partitions total variability into between-group and within-group components and uses their ratio to determine whether observed mean differences exceed chance, giving learners the conceptual foundation for interpreting ANOVA results.
Covers the one-way ANOVA procedure — involving a single independent variable — walking learners through the hypotheses, sum-of-squares calculations, ANOVA table construction, and decision rules for testing whether group means differ significantly.
Extends ANOVA to designs with two or more independent variables (two-way ANOVA), explaining main effects and interaction effects so learners can analyze situations where multiple factors simultaneously influence an outcome.
Covers post-hoc tests (e.g., Tukey, Bonferroni) used after a significant omnibus F-test to identify which specific group pairs differ, guiding learners and instructors on how to fully interpret and report ANOVA results.
A 528-question bank spanning probability, statistics, and inferential concepts such as population vs. sample identification, Venn diagrams, and descriptive vs. inferential statistics, which instructors draw from to build quizzes and assessments throughout the course.