Example of Comparisons

An electronics design engineer studies the effect of operating temperature and three types of face-plate glass on the light output of an oscilloscope tube. The engineer has performed Fit General Linear Model and then uses Comparisons to determine whether the mean differences between pairs of glass types are statistically significant and to estimate those differences.

  1. Open the sample data, LightOutput.MTW.
  2. Choose Stat > ANOVA > General Linear Model > Comparisons.
  3. From Response, select LightOutput.
  4. Under Type of comparison, select Pairwise.
  5. Under Method, select Tukey.
  6. Under Choose terms for comparisons, double-click GlassType.
  7. Click Graphs.
  8. Check Interval plot for differences of means.
  9. Click OK in each dialog box.

Interpret the results

The interval plot of the differences shows that the mean difference between the light output for GlassType 1 and GlassType 2 is statistically significant because the interval labeled "2-1" does not contain zero.

The grouping information table also indicates that this difference is statistically significant because the two groups do not share a letter. This table shows that the mean for GlassType 1 is 1087.33 and the mean for GlassType 2 is 1035.00.

Grouping Information Using the Tukey Method and 95% Confidence

GlassTypeNMeanGrouping
191087.33A 
391054.67AB
291035.00  B
Means that do not share a letter are significantly different.