To do the JMP:

The key thing to understand is that you will type all the scores down the first column.  Double-click Column 1 and give it a name that describes the variable both scores are measuring.  Here, that is GPA.  Type all the GPA scores for High School A down Column 1, and then continue to type all the GPA scores down Column 1 for High School B.  That means you should have a total of 15 rows when you are done 7 scores from A and 8 scores from B.  Be careful, don't accidentally enter the means or standard deviations as data.

Now double-click the region at the top to the right of Column 1 to create a new column.  Call that column High School and type A repeatedly down column 2 in all 7 rows that have scores from High School A in Column 1.  Then type B in the rest of the rows. I suggest you type your first word, then copy and paste it in all the other relevant cells in Column 2, then type your second word and copy and paste it to ensure there are no typos.

Thus, I would have two columns of data.  The first column shows all the numerical data scores (all the GPA scores) and the second column labels the data in the first column telling me which group the scores belong to (A or B).

Right-click Column 1 and select "Column Info" and confirm that its Data Type is Numeric and its Modeling Type is Continuous, changing the settings if necessary.  Right -click Column 2 and select "Column Info" and confirm that its Data Type is Character and its Modeling Type is Nominal, changing the settings if necessary.

Now select "Analyze, Fit Y By X".  Select GPA and click Y, Response and select High School and click X, Factor.  Click OK. 

You will see a graph with dots plotted representing all the scores in two columns.  If you don't see two columns of dots for the two samples, you have not labelled your data correctly!   Close the screen and go back to your data table.  Follow my steps above to right-click each column and select Column Info, and make sure that the Data Type for GPA is Numeric and its Modeling Type is Continuous, changing the settings if necessary.  Repeat for High School, and confirm that its Data Type is Character and its Modeling Type is Nominal, changing the settings if necessary.

Once you have the graph showing the vertical array of dots for your two samples, you are ready to analyze the data.

Click the red triangle and select Means and Std Dev to get a summary of the means and standard deviations.   Look at the standard deviations in this output and use your Rule of Thumb to decide if you wish to use the pooled test or conservative (unpooled) test.  Of course, these values for the mean and standard deviations should match what you were given at the start (if rounded accordingly).

Click the red triangle and select Display Options and select Box Plots if they have requested side-by-side boxplots (not requested for this question). 

Click the red triangle and select Means/Anova/Pooled t to get JMP to do the pooled two-sample t test.  Click the red triangle again and select t-Test to get JMP to do the generalized two-sample t test (not pooling). You will note that, when JMP does the pooled t-test, it says, under the "t Test" title bar, "Assuming equal variances."  When JMP does the generalized t-test, it says, under the "t Test title bar, "Assuming unequal variances."

Look carefully at the JMP printouts to confirm if it is doing "HA- HB" like you did earlier in the question.  I  believe it will do so.  If, however, it is doing "HB- HA", note that that is fine, too.  But that would mean everything is backwards.  The confidence interval limits will have the wrong signs, and be the wrong way around.  The test statistic will have the wrong sign.  Finally, the P-value for an upper-tailed test would now be the P-value for a lower-tailed test.

JMP does not know whether you are doing an upper-tailed, lower-tailed or two-tailed test, so it gives you the P-value for all three.  You have to be clear yourself what the alternative hypothesis is, and therefore which of the three P-values are correct. 

They want you to get the critical value and state the decision rule here.

I tell you the hypotheses we test in Anova in Lesson 5.

Compare the medians (the lines shown inside the boxes of the boxplots).  Are they all pretty similar? Or does at least one appear to be considerably different from the others?  This is an estimate of what may be the case for the population means, too.

When they ask for the values of ni, all they mean is tell them what n1 equals, n2 equals, n3 equals.  Example, n1=5, n2=8, and n3=6. (I think, but everyone may have different data sets.)  Of course, tell them I and N, too.

Part (e)

This question should be done by hand (i.e. with your calculator, not with JMP ).  You are given the three means and standard deviations then do as I do in my Lesson 5, questions 1 and 2.  Follow my example to compute the overall mean, SSG, MSG, SSE, SSE, and the F statistic.

You will then be able to check your answers when you use JMP.  Note that your answers may be slightly different than JMP's since you have used rounded off values for the means and standard deviations.

Personally, I would just write it in text like this, "SSG = 5(16-30) + 4(12-30) + ..." (I am making up those numbers.)  Then MSG = SSG/DFG = 51/2 = etc.  You can also use the Math Input button in the toolbar if you want to get fancy (but it is so slow.....).

Put bounds on the P-value using Table E, like I do in my questions 1 and 2.

They want the pooled sample standard deviation here.  The square root of MSE.