Independent t-test
Hypothesis tests · Method and input reference
Two-sided; independent t uses Welch. Paired tests require matched observations. Permutation uses difference in means, 9,999 resamples and a fixed seed. Effect sizes use pooled sample SD. Synthetic example: Two independent blood-pressure cohorts: 120 and 96 people, with unequal variability; values in mmHg.
Open calculator · Compare methods in the decision matrix
When to consider it
- Compare means in two independent groups with Welch’s t-test.
Assumptions and scope
- Observations must be independent between subjects; repeated rows from one subject are not independent samples.
- Check outliers and whether mean-based inference is suitable for the sample sizes and distributions. Do not select a test solely from a normality-test p-value.
Uses Welch; no pooled-variance option.
Required inputs
- Observations — Numeric observations; preserve the row and column structure described above.
- Second sample — Numeric observations; preserve the row and column structure described above.
Review missing values and data coding before running. Sample inputs are synthetic teaching examples.
Implementation
Lifescio validates inputs and formats results; listed functions are the principal calculation routines, not an exhaustive transitive dependency list.
- scipy 1.15.3: scipy.stats.ttest_ind
These are pinned library versions; saved results record the versions actually used at runtime.