We will look at comparing medians of Customer Satisfaction by Customer Type, using the Two
Sample Mann-Whitney test with H0: Median Difference = 0, Ha: Median Difference ≠ 0. The Two
Sample Mann-Whitney Test is the nonparametric equivalent to the parametric Two Sample t-Test
(i.e., Two Sample t-Test on Ranks). The test does not assume sample normality but does
assume that the samples have equal shapes. If the shapes are different, the null hypothesis
is that the distributions are the same.
The optional Two Sample KS (Kolmogorov-Smirnov) test is used to compare the distributions of
two samples. The test is H0: Distribution (CDF) Difference = 0, Ha: Distribution (CDF)
Difference ≠ 0. The CDF is the Cumulative Distribution Function. The two-sided test
statistic is the maximum absolute difference between the CDF values as shown:
Note this graph may be recreated using SigmaXL > Graphical Tools > Empirical/Normal CDF
Plots. Display Normal CDF Plots is unchecked. Copy and Paste Customer Type 3 plot into
Customer Type 2. Adjust legend and axis labels.
Two Sample Mann-Whitney Test (with 2 Sample KS Option)
Open Customer Data.xlsx, click Sheet 1 tab (or press
F4 to activate last worksheet).
Click SigmaXL > Statistical Tools > Nonparametric Tests > 2 Sample
Mann-Whitney.
If necessary, check Use Entire Data Table, click Next.
With Stacked Column Format checked, select Overall
Satisfaction, click Numeric Data Variable (Y) >>; select
Customer Type, click Group Category (X) >>; and
Ha:Not Equal To. Check Display 2 Sample
KS.
Click OK. Select Customer Type 2 and 3.
Click OK. The resulting output for the 2 Sample Mann-Whitney test
is:
Given the p-value of .0008 we reject H0 and conclude that Median Customer Satisfaction
is significantly different between Customer types 2 and 3. This confirms previous
findings and matches the results of the 2 Sample t-Test.
The resulting output for 2 Sample KS test is:
Given the P-Value of .0035 we reject H0 and conclude that the Satisfaction distributions
are significantly different between Customer types 2 and 3.
This agrees with the results for the Mann-Whitney test.