Final answer:
A null hypothesis for a chi-squared test might state that the populations of two datasets come from the same distribution, in line with a test for homogeneity.
Step-by-step explanation:
One null hypothesis that might be analysed by a chi-squared test is that the populations of two datasets come from the same distribution, which is known as the test for homogeneity.
When evaluating whether there is a significant difference between the populations, the observed frequencies from the datasets are compared against the expected frequencies, assuming that both populations are from the same distribution.
For instance, if we want to analyse whether two different brands of chocolate are equally preferred across genders, the null hypothesis would be that there is no difference in preference between the brands across genders.
One null hypothesis that can be analyzed by a chi-squared test is whether the distribution of two populations is the same, even if the specific distribution is unknown.
This is referred to as the test for homogeneity. The null hypothesis asserts that the populations of the two data sets come from the same distribution. The test compares the observed values against the expected values if the populations followed the same distribution.