# square

… a statistical test of selections from a pool

### square calculates the statistical significance of disparities in an employment selection process when applicant flow data is available.

**square** computes probability values using the Chi-Square test and, for 2x2 tables, Fisher's Exact Test. For example, in a race/hiring case, **square** determines if there is a significant disparity in the rates at which blacks and whites are hired.

When this probability is sufficiently low (*i.e.*, .05 or less), the result is said to be statistically significant. Disparities that are statistically significant are generally recognized as evidence of discrimination.

### Overview of Process

**square** creates tables of rows and columns to analyze a selection process. By default, a 2x2 table is created, but you may create a table with up to 5 rows and 6 columns. You provide a title for the table, select one of the Display Options, and enter descriptive labels (*e.g.*, Black, White, Hired, Not Hired) for the rows and columns.

Finally, you enter data into the individual cells and click the Calculate button to have **square** compute the results, which are reported in the Statistics box. The results may be printed or saved.

### In the example below …

A charge has been filed against the XYZ Co. alleging race discrimination in hiring. We know who applied and who was hired: about 16 percent of black applicants were hired compared with 38 percent of white applicants.

**square** shows this disparity to be statistically significant, with a probability of 3 in 10,000 for the two-tail Fisher's Exact Test. As a rule, probabilities less than 0.05, or 5 in 100, are considered statistically significant.

*— click image to expand*