d of 0.175, a small effect size. Why is this information useful for planning the sample size for the main study?
]]>t test yet (that will happen in Chapter 9), but you often won’t know the meaning of a particular statistic when reading the results of a research study. When you encounter a new test statistic, you can always interpret the *p* value in the same way. What do we know from the *p* value here? (Note: The *p* value is related to the difference between the two means, 0.39 and 1.52.)
]]>p value is less than the alpha level of 0.05, so we reject the null hypothesis; we have evidence that the mean attitude change among those in the perspective-taking condition is less than the mean attitude change in the control condition.
]]>p value is less than the alpha level of 0.05, so we fail to reject the null hypothesis; we cannot conclude that the mean attitude change among those in the perspective-taking condition is less than the mean attitude change in the control condition.
]]>p value is greater than the alpha level of 0.05, so we reject the null hypothesis; we have evidence that the mean attitude change among those in the perspective-taking condition is less than the mean attitude change in the control condition.
]]>p value is greater than the alpha level of 0.05, so we fail to reject the null hypothesis; we cannot conclude that the mean attitude change among those in the perspective-taking condition is less than the mean attitude change in the control condition.
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