obitools4/autodoc/docmd/pkg/obistats/ttest.md

Statistical Hypothesis Testing Module (obistats)

This Go package provides implementations of common t-tests for comparing sample means under different assumptions. It supports one- and two-sample tests, paired or unpaired designs.

Core Types

• TTestResult: Encapsulates the outcome of a t-test, including:

  • Sample sizes (N1, N2)
  • Test statistic value (T)
  • Degrees of freedom (DoF)
  • Alternative hypothesis type (AltHypothesis: LocationDiffers, LocationLess, or LocationGreater)
  • Computed p-value (P)

• TTestSample interface: Requires methods Weight(), Mean(), and Variance() — enabling reuse with summary statistics.

Supported Tests

1. TwoSampleTTest(x1, x2)
   Standard Student’s t-test for two independent samples assuming equal variances and normality.

2. TwoSampleWelchTTest(x1, x2)
   Welch’s t-test for two independent samples without equal-variance assumption, using Satterthwaite approximation for degrees of freedom.

3. PairedTTest(x1, x2)
   Paired t-test for dependent samples (e.g., before/after), testing mean of differences against μ0.

4. OneSampleTTest(x)
   One-sample t-test comparing sample mean to a known population mean μ0.

Error Handling

• Returns errors for invalid inputs: zero sample size (ErrSampleSize), zero variance (ErrZeroVariance), or mismatched paired sample lengths (ErrMismatchedSamples).

Implementation Notes

• p-values are computed using the cumulative distribution function (CDF) of the Student’s t-distribution.
• Designed for statistical rigor and modularity, reusing internal utilities (e.g., Mean, StdDev) from a shared module.