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Learn R programming
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Module 9
Hypothesis Testing and Tidy Analysis
1
Understanding and Applying T-Tests
Perform and interpret one-sample, independent two-sample, and paired t-tests.
2
Chi-Square Test of Independence
Perform and interpret a chi-square test of independence.
3
One-Way ANOVA and Post-Hoc Tests
Perform and interpret a one-way ANOVA and appropriate post-hoc tests.
4
Non-Parametric Tests: Wilcoxon, Kruskal-Wallis, and Fisher's Exact
Apply non-parametric alternatives: Wilcoxon, Kruskal-Wallis, and Fisher's exact tests.
5
Tidying Model Outputs with `broom::tidy()`
Extract model results into a tidy data frame using `broom::tidy()`.
6
Interpreting broom::tidy() Output
Interpret key outputs from `broom::tidy()` (e.g., estimate, p.value, conf.low, conf.high).
7
Understanding Multiple Comparisons and Bonferroni Correction
Explain the problem of multiple comparisons and apply a Bonferroni correction.
Previous module
Foundations of Statistical Inference
Next module
Regression Modeling