The chi-square test is used to determine if there is a significant difference between the expected and observed frequencies in one or more categories. It involves: 1) collecting sample data on categories like handedness, 2) calculating the expected frequencies if there is no difference, 3) using a chi-square calculation to measure differences between expected and observed data, and 4) comparing the chi-square value to a critical value to determine if differences are likely due to chance or signify an actual significant difference between groups. In this example, the chi-square value was less than the critical value, so the test found no significant difference in handedness between men and women in the sample.