Then, for the First variable (deinopis data, for us), type the Sample size, Mean, and Standard deviation in the appropriate boxes. In the pop-up window that appears, select Summarized data. Under the Stat menu, select Basic Statistics, and then select 2-Sample t.: Since we've already learned how to ask Minitab to calculate a confidence interval for \(\mu_X-\mu_Y\) for both of those data arrangements, we'll take a look instead at the case in which the data are already summarized for us, as they are in the spider and prey example above. Again, the commands required depend on whether the data are entered in two columns, or the data are entered in one column with a grouping variable in a second column. We simply skip the step in which we click on the box Assume equal variances. Otherwise, they'll use the two-sample pooled \(t\)-interval.Īsking Minitab to calculate Welch's \(t\)-interval for \(\mu_X-\mu_Y\) require just a minor modification to the commands used in asking Minitab to calculate a two-sample pooled \(t\)-interval. Then they'll use Welch's \(t\)-interval for estimating \(\mu_X-\mu_Y\). Substituting in what we know, the degrees of freedom are calculated as: Let's calculate Welch's \(t\)-interval to see what we get. do those sample variances differ enough to lead us to believe that the population variances differ? If so, we should use Welch's \(t\) -interval instead of the two-sample pooled \(t\)-interval in estimating \(\mu_X-\mu_Y\).
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