T-test
A t-test is a statistical hypothesis test that uses a t-distributed statistic to assess a mean or difference in means under specified assumptions.
Statistics Slam Dunk
A t-test is a statistical test that evaluates whether a difference between means is unlikely under a null hypothesis, typically using a t-distributed test statistic.
- How it is used
- Tests whether two groups differ in average numeric outcomes for sports, treatment, and inequality questions.
- How deep it goes
- Defines two-group mean testing and works through R outputs, visualizations, thresholds, and record-count caveats without formal derivations.
- Examples
- Uses NBA home-road fouls and free throws, salary and win-share Gini coefficients, drugs, exam scores, and customer surveys.
- What you can do after
- Apply it via R's t.test() to compare two group means and make a threshold-based null-hypothesis decision.
Effective Data Analysis
A t-test is a statistical test that evaluates differences between means using a t-distributed test statistic.
- How it is used
- Uses a two-group mean comparison to assess differences relevant to analytics decisions.
- How deep it goes
- Defines independent and paired tests, illustrates assumptions and sample-size effects, and provides exercises for power analysis and testing.
- Examples
- Compares support metrics around a search change, simulated scores, and July temperatures in Boston and New York City.
- What you can do after
- Apply it via SciPy after checking assumptions and sample size, then summarize findings for a stakeholder.
Related concepts
- hypothesis testingkind of · Hypothesis testing is a formal statistical procedure that uses observed data to evaluate evidence about a specified hypothesis, often a null hypothesis.
- student's t-distributionuses · Student’s t-distribution is a family of continuous probability distributions with heavier tails than the normal distribution, used in inference when variability is estimated from data.
- analysis of variancecontrasts with · Analysis of variance is a statistical technique for assessing whether group means differ by partitioning observed variability among specified factors and residual error.
- experimentationuses · Experimentation is the deliberate testing of an idea, intervention, or alternative by observing outcomes to gather evidence or compare effects.
- Gini coefficientuses · A Gini coefficient is a summary measure of inequality derived from the area between a Lorenz curve and the line of perfect equality, typically ranging from zero for complete equality toward one for greater inequality.
- p-valueuses · A p-value is the probability, assuming a specified null hypothesis, of obtaining a test statistic or result at least as extreme as the observed one.
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