11.3.2 - Minitab Express: Test of Independence
If you have a data file with the responses for individual cases then you have "raw data" and can follow the directions below. If you have a table filled with data, then you have "summarized data." There is an example of conducting a chi-square test of independence using summarized data on a later page. After data entry the procedure is the same for both data entry methods.
MinitabExpress – Chi-square Test Using Raw Data
Research question: Is there a relationship between where a student sits in class and whether they have ever cheated?
Null hypothesis: Seat location and cheating are not related in the population.
Alternative hypothesis: Seat location and cheating are related in the population.
To perform a chi-square test of independence in Minitab Express using raw data:
- Open Minitab data set
- On a PC: Select STATISTICS > Cross Tabulation and Chi-Square
On a Mac: Select Statistics > Tables > Cross Tabulation and Chi-Square
- Double-click on the variable Seating to insert it into the Rows box
- Double-click on the variable Ever Cheat to insert it into the Columns box
- Click the Display tab and check the boxes Chi-square test for association and Expected cell counts
- Click OK
This should result in the following output:
Cell contents grouped by Back, Front, Middle, All; First row: count, Next row: expected count
Select your operating system below to see a step-by-step guide for this example.
All expected values are at least 5 so we can use the Pearson chi-square test statistic. Our results are \(\chi^2 (2) = 1.54\). \(p = 0.4633\). Because our \(p\) value is greater than the standard alpha level of 0.05, we fail to reject the null hypothesis. There is not evidence of a relationship in the population between seat location and whether a student has cheated.