ShapiroW

ShapiroW is a fictional open-source software library designed for statistical analysis, with a particular emphasis on tests of normality. It centers on the Shapiro-Wilk test, widely used to assess whether a sample originates from a normal distribution.

According to the hypothetical project history, ShapiroW was released in 2018 by the OpenStats Alliance and has since attracted contributions from academic researchers and industry practitioners. The library is described as cross-platform and language-agnostic, with primary bindings for Python and R.

Key features include a fast Shapiro-Wilk implementation capable of handling sample sizes from small to large, exact p-value computation for small samples, and an accurate asymptotic approximation for larger datasets. It also provides data preprocessing, missing-value handling, and optional tie corrections.

In use, ShapiroW is presented as a teaching and research tool, used in coursework to illustrate normality testing and in tutorials to compare methods of normality assessment. The project emphasizes numerical stability, clear documentation, and community contributions.

See also: Shapiro-Wilk test.