Stat 2000: Tips for Web Assign HW 11
Published: Thu, 03/17/11
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General Tips for Web Assign and JMP
When working with Web Assign, always enter the answer to one specific box and then click "Submit Answer" to confirm that is correct before you move on to another box. Do not enter several answers all at once in several boxes before you click "Submit Answer". You risk being marked wrong due to some typo or something.
For some strange reason, JMP 8 occasionally computes wrong answers even if you have copied and pasted your data correctly. I suggest that, if it is feasible, type the given data into your calculator (in Stat mode as shown in Appendix D of my book), and have your calculator compute the sample mean. Compare that answer with JMP's answer for the sample mean. If they are the same, everything is fine. If they are not the same, close JMP 8 and restart it, recopy and paste the data, and check again. Sometimes you have to do this 2 or 3 times before JMP finally works. If it is not feasible to use your calculator to compute the sample mean, have JMP do the question 2 or 3 times, being sure to restart JMP and recopy the data each time, and confirm that JMP gives you the same answer each time before risking entering the results into Web Assign.
If you are taking the course by distance/online (Section D01) click here to see your tips for HW 11.
There are no tips for HW11 at this time. I will send tips later when the assignment is posted.
Study Lesson 8 in my book, if you have it, to prepare for this assignment. If you do not have the current edition of my Basic Stats 2 book, I strongly recommend you purchase Volume 2 because the changes have been vast and are addressing changes the course has undergone in the last few years.
In question 1, the joint distribution is simply the joint proportions found by
dividing the appropriate cell count by the Grand Total, and the marginal
distribution is the marginal proportions found by dividing the
appropriate row or column total by the Grand Total. I discuss this in more
detail at the start of Lesson 8 in my new edition only.
Question 2 is playing with
the concepts I discuss in question 4 of Lesson 8.
In question 3, I would
contend that two of the choices they give you for the hypotheses are correct,
but they would disagree. When you are comparing two groups (men and women; old
and young; two cities in this case), saying the rows and columns are independent
is equivalent to saying the distribution for the one group is the same as the
distribution for the other group. For example, in my question 2 in Lesson 8
where we are comparing the attitudes towards shopping for men and women, the
null hypothesis is that your attitude towards shopping is independent of your
sex. We could also say that the distribution in attitudes is the same for men
and for women. Note, that is not the same as saying the percentages are all
equally likely. Just that the distributions are the same. For example, if the
population of men has 20% who always like shopping, 30% who sometimes like
shopping, and 50% who never like shopping, then the null hypothesis would same
that the women would also have the same distribution as the men (they too would
have the 20% / 30% / 50% distribution. Admittedly, one of the choices
they offer you in this question that I would consider correct is a little vague,
and for that reason, I can see why the other one is preferred.
Question 4. To enter this
data in JMP. Click New Data Table. You will need a total of three columns.
Double-click Column 1 and name it "Music" and change the Data Type to
"Character" and the Modeling Type to "Nominal". Double click the space to the
right of the Music column to create a new column. Name that column "Movies" and
change the Data Type to "Character" and the Modeling Type to "Nominal". Double
click the space to the right of the Movies column to create a new column. Name
that column "Count" and keep the Data Type as "Numeric" but change the Modeling
Type to "Nominal".
Each row in the JMP data table is used to
enter the information for a particular cell of the two-way table. The first row
will represent the 1,1 cell; the second row will represent the 1,2 cell; etc.
For example, your 1,1 cell gives you the observed count for the young adults who
prefer Contemporary music and Action movies. In the JMP data table, in row 1
type "Contemporary" in the Music column, "Action" in the Movies column, and type
the given observed count in the "Count" column. Type the info for the 1,2 cell
into the second row of your JMP table. That is the observed count for the young
adults who prefer Contemporary music and Comedy movies, so you will type
"Contemporary" in the Music column, "Comedy" in the Movies column and the
observed count in the Count column. In the third row you will type Contemporary
in the Music column, Drama in the Movies column, and the observed count for the
1,3 cell in the Count column. Continue in this fashion all the way to the
sixteenth row where you will type "Rock" in the Music column, "Horror" in the
Movies column, and the observed count for the 4,4 cell in the Count
column.
You will notice that the first two columns
of the JMP table are used to specify which row and column of the two-way table
you are talking about, and the third column enters the observed count for that
particular cell.
Once you have entered in all the observed
counts, select Analyze, Fit Y By X. Select "Movies" and click "Y, Response",
select "Music" and click "X, Factor", and select "Count" and click "Freq".
Click "OK". Click the red triangle next to "Contingency Analysis of Music by
Movies" at the top and deselect "Mosaic Plot" to remove that from the output.
You now see a Contingency Table (or two-way table) and the "Tests" below it.
Click the red triangle next to Contingency Table and make sure that all that is
select is "Count", "Expected" and "Cell Chi Square" to display those values in
each cell of the table. Note the Pearson ChiSquare is the test statistic for
the problem (in the last row of the "Tests" output) and the Prob>ChiSq is the
P-value for that test.
When they ask what two
cells contribute most to the test statistic, they are asking which two cells
have the largest chi-square values.