Test for homogeneity is another chi-square-based test determining if two or more populations have similar distributions of a categorical variable. In contrast, the other two chi-square tests, the goodness-of-fit and the test for independence, deal with the data from a single population. Suppose researchers wish to study the susceptibility of carriers of sickle cell anemia to malaria infection and compare it with people with normal RBCs. The null hypothesis states that people with normal RBCs and carriers of sickle cell anemia are equally susceptible to malaria infection, while the alternate hypothesis states the contrary. Since the infection rates of two independent populations are compared, a test for homogeneity is required instead of a test for independence. This test uses calculations similar to other chi-square-based methods to determine the chi-square value and P-value. The null hypothesis is rejected as the chi-square value exceeds the critical value. This means that there is sufficient evidence to conclude that people with normal RBCs and carriers of the sickle cell anemia trait are not equally susceptible to malaria.