Using your results from JMP INTRO, carry out a complete hypothesis test for each age using one of the commonly used significance levels. Repeat this analysis, using the second data set HTWT15.jmp, a sample of 15-year-olds. JMP INTRO provides a p-value for a twosided test. The p-value is in the line of output above this, Prob > F. For the two-sample t-test, the test statistic is the last line of the display of this test. Although you don t need to worry about the variance test analysis, if you want to find out more information about this analysis, click on the question mark icon, and when the cursor changes to a question mark, click somewhere in the Tests that the Variances are Equal area. This causes a test to be done for whether the variances are equal, but it also displays the output necessary for the two-sample t-test. To continue with the analysis, select UnEqual Variances from the pop-up red triangle menu from Oneway Analysis of By Gender. Because Gender is categorical, this produces side-by-side vertical dotplots for the two gender groups. To compare means, choose Analyze fi Fit Y by X with as the Y,Response variable and Gender as the X,Factor. Look at the displays of the data to see if the conditions for using the two-sample t test are reasonable. Choose Analyze fi Distribution using as the Y,Columns variable By Gender. Open JMP INTRO, and from the JMP Starter menu, select Open Data Table. You will also be given data for the heights of a random sample of 15-year-old males and females from a high school. You will be given data for the heights of a random sample of 12-year-old males and females from a middle school.
You are going to examine if the mean heights for 12-year-old and 15-year-old adolescent males is greater than the mean heights for similarly aged females. 1 JMP INTRO Lab Activities Lab Activity Hypothesis Testing Two-Sample t-test Data Sets: HTWT12.jmp and HTWT15.jmp It is well known that mean height for adult males is greater than for females.
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