Data & AnalyticsTechnologyPlatinum

Choose and interpret statistical tests for research data.

Hypothesis Testing Expert

Statistical tests, sample size, p-values

intermediatev5.0

Best for

▸Selecting appropriate statistical test for comparing group means in A/B experiments
▸Validating normality and homoscedasticity assumptions before running ANOVA
▸Calculating minimum sample sizes for detecting meaningful effect sizes in user research
▸Interpreting p-values and confidence intervals without falling into statistical significance fallacies

What you'll get

▸Structured test selection flowchart with assumption checks, Python/R code for validation, and interpretation guidelines
▸Power analysis report with sample size recommendations, effect size justifications, and business impact context
▸Complete hypothesis testing workflow from formulation through results interpretation with statistical and practical significance assessment

Expects

Clear research question, data types (continuous/categorical), sample characteristics, and practical significance thresholds for the business context.

Returns

Step-by-step statistical test selection, assumption validation code, sample size calculations, and interpretation framework with effect size context.

What's inside

“You are a Senior Applied Statistician. You guide researchers through hypothesis testing from research question to actionable interpretation, prioritizing effect sizes and confidence intervals over p-values. - Report effect sizes with confidence intervals as primary results; p-values are supplementar...”

Covers

What You Do DifferentlyMethodologyWatch For

Not designed for ↓

×Machine learning model evaluation or predictive modeling tasks
×Causal inference from observational data without experimental design
×Time series analysis or forecasting statistical methods
×Bayesian statistical inference or posterior probability calculations

SupaScore

89.45▼

Research Quality (15%)

9.25

Prompt Engineering (25%)

8.85

Practical Utility (15%)

8.7

Completeness (10%)

9.4

User Satisfaction (20%)

8.9

Decision Usefulness (15%)

8.8

Evidence Policy

Standard: no explicit evidence policy.

hypothesis-testingstatisticsp-valuesignificance-testinganovat-testchi-squarepower-analysiseffect-sizeab-testingscipy

Research Foundation: 8 sources (3 books, 2 official docs, 2 academic, 1 industry frameworks)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.