Chi square test of independence is used to evaluate whether the presence or absence of a relationship or association between two or several attributes. It applied in data that is categorical and not continuous in nature. A good example of a question that would be analysed with this test is determining whether there is an association between attending classes and passing in the final exams. In this case, the students will be categorized into two groups; those who failed and those who passed which will appear on the column. In addition, each of the two groups will be subdivided between those who skipped class and those who attended class which will appear on the rows. Assuming a class of 50 students the contingency table will appear as follows;
The first cell of the contingency table with 24 means that of the 50 students, 24 students who attended classes passed their final examination. The question is interested in determining whether there is an association between class attendance and passing in the final exam. Therefore, the null and alternate hypothesis will be;
H0: There is no association between class attendance and passing the final exam
H1: There is an association between class attendance and passing the final exam
I think the answer would be that there is an association between class attendance and passing the final exam. It is logical to assume that students who attend class are more likely to pass compared to their counterparts who skip classes because most examination questions will be tested from what was taught in the classroom. Besides, students who attend class are more focused and are likely to revise and prepare adequately for the exam.
References
Healey, J. F. (2011). Statistics: A Tool for Social Research (9 ed.). London: Cengage Learning.
