Basic Analysis and Graphing - SAS

Chapter 5 Performing Oneway Analysis 129
Overview of Oneway Analysis
Overview of Oneway Analysis
A one-way analysis of variance tests for differences between group means. The total variability in the
response is partitioned into two parts: within-group variability and between-group variability. If the
between-group variability is large relative to the within-group variability, then the differences between the
group means are considered to be significant.
Example of Oneway Analysis
This example uses the Analgesics.jmp sample data table. Thirty-three subjects were administered three
different types of analgesics (A, B, and C). The subjects were asked to rate their pain levels on a sliding scale.
You want to find out if the means for A, B, and C are significantly different.
1. Open the Analgesics.jmp sample data table.
2. Select Analyze > Fit Y by X.
3. Select pain and click Y, Response.
4. Select drug and click X, Factor.
5. Click OK.
Figure 5.2 Example of Oneway Analysis
You notice that one drug (A) has consistently lower scores than the other drugs. You also notice that the
x-axis ticks are unequally spaced. The length between the ticks is proportional to the number of scores
(observations) for each drug.
Perform an analysis of variance on the data.
6. From the red triangle menu for Oneway Analysis, select Means/Anova.
Note: If the X factor has only two levels, the Means/Anova option appears as Means/Anova/Pooled t,
and adds a pooled t-test report to the report window.