A graduate-level computer science course only gives the grades of A, B, or C. The department has determined that there should be
40% A’s given, 40% B’s given and 20% C’s given as final grades for the course. For the spring 2020 semester, 200 students took the course and 100 students received A’s, 50 students received B’s and 50 students received C’s, so those are my observed frequencies. We want to do a Chi-square Multinomial Goodness of Fit test to see if our grading guidelines match up with what is actually happening. The p-value for this hypothesis test is = 0.000. Make your decision to reject the null hypothesis or not, state that decision, and explain what that decision means in this specific context.
The null hypothesis: The department has determined that there should be 40% A’s given, 40% B’s given and 20% C’s given as final grades for the course
If the p-value for this hypothesis test is = 0.000... and this number is lower than the 0.05 significance level, we reject the null hypothesis and conclude that from the result of our observation that final grades do not match this grading guidelines.
It means the grading guidelines was exceeded in terms of As, was less in terms of Bs and was higher in terms of Cs i e the grading guidelines was not consistent with what was stated in the null.
