Between-patient designs and continuous data

In this setting there is a technique, termed one-way analysis of variance (one-way ANOVA), which gives an overall p-value for the simultaneous comparison of all of the treatments. Suppose, for example, we have four treatment groups with means Pi, p2 P 3 P4. This procedure gives a p-value for the null hypothesis  

A significant p-value from this test would cause us to reject the null hypothesis, but the conclusion from this only tells us that there are some differences somewhere at least two of the ps are different. At that point we would want to look to identify where those differences lie and this would lead us to pairwise comparisons of the 

For example, let us suppose that we have three treatment groups test treatment ( jLi), active control (1X2) and placebo (p.3). In a superiority setting there are two questions of interest  

Is the test treatment better than the control treatment  

Both of these questions are answered by the unpaired t-test. 

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