{"enrichment":{"faq":[{"a":"Statistical Hypothesis Testing enables you to conduct t-tests for comparing two group means and ANOVA for analyzing multiple groups. Use t-tests to determine if differences between independent or paired samples are statistically significant, and ANOVA to test whether means across three or more groups differ significantly. The skill calculates test statistics and p-values to support your conclusions.","q":"How do I do t-test and ANOVA with Statistical Hypothesis Testing?"},{"a":"Statistical Hypothesis Testing uses p-value significance testing to quantify the probability that observed results occurred by chance under the null hypothesis. A low p-value (typically <0.05) suggests your findings are statistically significant. This metric is central to validating data-driven decisions and determining whether group differences are real or random variation.","q":"What is p-value significance testing and why does it matter?"},{"a":"Statistical Hypothesis Testing calculates p-values and effect sizes to analyze A/B test results, helping you determine if observed differences between control and treatment groups are statistically significant. The skill supports comparing group means, computing confidence intervals, and assessing practical significance alongside statistical significance for robust test interpretation.","q":"How does Statistical Hypothesis Testing analyze A/B test results?"},{"a":"Statistical Hypothesis Testing guides test selection based on your data characteristics. Use parametric tests like t-tests and ANOVA when data is normally distributed; use non-parametric alternatives like Mann-Whitney U or Kruskal-Wallis when normality assumptions are violated. The skill helps you choose the appropriate test based on data type and distribution properties.","q":"When should I use parametric vs non-parametric tests?"},{"a":"Statistical Hypothesis Testing computes effect sizes (such as Cohen's d) and confidence intervals to quantify the magnitude and precision of your findings. These metrics complement p-values by showing practical significance and the range of plausible population values, enabling more complete interpretation of hypothesis test results.","q":"How do I calculate effect sizes and confidence intervals?"},{"a":"Statistical Hypothesis Testing includes chi-square tests for assessing independence between categorical variables. It also supports multiple testing corrections like Bonferroni to control false positives when conducting many tests, and normality checks via Shapiro-Wilk to verify parametric test assumptions before analysis.","q":"What statistical tests does this skill support for categorical data?"}],"shadow_tags":["statistical-inference","ab-testing","parametric-tests","nonparametric-methods","effect-magnitude","significance-threshold","data-validation","distribution-analysis","variance-comparison"],"summary_rewrite":"Perform rigorous statistical tests including t-tests, ANOVA, chi-square, and non-parametric alternatives to assess whether observed differences are statistically significant. The skill handles independent and paired comparisons, multiple group analysis, categorical independence testing, and includes effect size calculations, confidence intervals, and power analysis to support evidence-based decision-making."},"files":[{"bytes":7650,"path":"skills/statistical-hypothesis-testing/SKILL.md","sha256":"2dd6c68cb2e8bb46eaf3be97684845c670ca6ca129c4ee84480e7272b327d983","url":"https://skillfed.io/files/aj-geddes/useful-ai-prompts/statistical-hypothesis-testing/586ba7b8/SKILL.md"}],"id":"aj-geddes/useful-ai-prompts/statistical-hypothesis-testing","links":{"html":"https://skillfed.io/aj-geddes/useful-ai-prompts/statistical-hypothesis-testing","md":"https://skillfed.io/aj-geddes/useful-ai-prompts/statistical-hypothesis-testing.md","repo":"https://github.com/aj-geddes/useful-ai-prompts"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":45,"language":"Shell","last_updated":"2026-03-04","license":"MIT","name":"Statistical Hypothesis Testing","publisher":"aj-geddes","stars":299},"relations":{"similar":[{"id":"beita6969/ScienceClaw/data-stats-analysis"},{"id":"aj-geddes/useful-ai-prompts/ab-test-analysis"},{"id":"beita6969/ScienceClaw/scipy-analysis"},{"id":"foryourhealth111-pixel/Vibe-Skills/statistics-math"},{"id":"pluginagentmarketplace/custom-plugin-data-engineer/statistics-math"},{"id":"wangyendt/wayne-skills/statistics"},{"id":"beita6969/ScienceClaw/statsmodels-stats"},{"id":"foryourhealth111-pixel/Vibe-Skills/statistical-analysis"},{"id":"synthetic-sciences/openscience/statistical-analysis"},{"id":"zLanqing/codex-claude-academic-skills/statistical-analysis"}]},"slug":{"owner":"aj-geddes","repo":"useful-ai-prompts","skill":"statistical-hypothesis-testing"},"version":"586ba7b8"}