# 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:

1. Open Minitab data set
2. On a PC: Select STATISTICS > Cross Tabulation and Chi-Square
On a Mac: Select Statistics > Tables > Cross Tabulation and Chi-Square
3. Double-click on the variable Seating to insert it into the Rows box
4. Double-click on the variable Ever Cheat to insert it into the Columns box
5. Click the Display tab and check the boxes Chi-square test for association and Expected cell counts
6. Click OK

This should result in the following output:

Cell contents grouped by Back, Front, Middle, All; First row: count, Next row: expected count

No Yes All 24 8 32 24.21 7.79 38 8 46 34.81 11.19 109 39 148 111.98 36.02 1714 55 226
Chi-Square DF P-Value 1.54 2 0.4633 1.63 2 0.4435
Video Walkthrough

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.