You supervise two outpatient facilities and want to compare the patient satisfaction at each. You decide that a score of 8.5, or better, out of 10 will be considered “good satisfaction”, and a score of less than 8.5, out of 10, will be considered “poor satisfaction”. You conduct a survey of patients at each facility over the same three month interval and gather the following data:
# with average score 8.5 or higher |
# with average score 8.4 or lower |
Total |
|
Facility #1 |
437 |
154 |
591 |
Facility #2 |
353 |
164 |
517 |
Total |
790 |
318 |
1,108 |
You perform a chi square test to determine whether the differences in scores are independent of the facility from which they came.
You will have to calculate the expected values for each of the cells (lecture 14, slides 4, 5). It would be nice if Excel could calculate the expected values from the actual data … but it doesn’t L.
In Excel, create two 2x2 tables; one with the actual values and one with the expected values. Use the CHISQ.TEST function to calculate the chi square value for the data.
When selecting the “Actual range” and the “Expected range” for your data entry, select the 2x2 values (not including the totals) for *both* of the facilities for the actual range and select the 2x2 values (not including the totals) for *both* of the facilities for the expected range.
E.g., for the actual range, you’d select the bolded cells:
# with average score 8.5 or higher |
# with average score 8.4 or lower |
Total |
|
Facility #1 |
437 |
154 |
591 |
Facility #2 |
353 |
164 |
517 |
Total |
790 |
318 |
1,108 |
Similarly, for the expected range (selected from the table of expected values that you created).
The result that Excel displays when you run the chi square test is the p-value. You don’t have to do anything else. ]
(a)
(b) Since the p- value < 0.05, the result is significant. The differences in scores are dependent on the facility from which they came.
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