Final answer:
The term 'sample size (n)' refers to the total number of observations or participants in a study, which, in this case, is the number of students in an English class. It is not related to the p-value, degrees of freedom, or the significance level in a chi-square test of independence.
Step-by-step explanation:
In a chi-square test examining the independence between variables such as class and grade among English students, the term "sample size (n)" represents the total number of observations within the study. Specifically, in this context, it would be the number of students in the English class being studied. It is important to note that the sample size is distinct from the p-value, degrees of freedom, or significance level, which are other aspects of hypothesis testing in statistics.
The degrees of freedom for a chi-square test of independence are calculated based on the number of categories in the variables being tested and are not simply the sample size minus one. This is different from some other statistical tests, such as the t-test, where the degrees of freedom are calculated as the sample size minus one (df = n - 1).
When conducting a chi-square test of independence, one prepares a contingency table of observed frequencies and computes the expected frequencies based on the assumption of independence between the variables. The chi-square statistic is then calculated to determine if the observed frequencies are significantly different from the expected frequencies.