Chi-Square Test

Often researchers use the chi‐square test in genetics for tests of Hardy‐Weinberg equilibrium and for comparing expected and observed offspring phenotypes. The chi‐square test is used on categorical variables. The chi‐square test examines the difference between expected and observed distributions. Specifically, this chapter looks at a goodness‐of‐fit test, comparing the expected frequency (which is the value that we expect to see based on the literature background material or a hypothesis generated as part of an experiment) to the observed frequency (which is the value actually observed as part of an experiment or study). The following assumptions must be satisfied in order to run a chi‐square: data type; and independence. In the chapter, statistical programs are used to perform a chi‐square test and determine significance. And also, the relationship between the observed and expected is evaluated and a logical conclusion for each scenario is constructed.