Stat 1000: Tips for Assignment 3
Published: Sat, 09/22/12
Please note that my first midterm exam prep seminar for
Stat 1000 will be on Saturday, Oct. 6, in room 100 St. Paul's College,
from 9 am to 9 pm . I am not ready to take registrations yet,
but I just wanted to give you a heads-up in case you need to make
arrangements to come. I will contact you later on when I am ready to
take registrations.
Did you miss my Tips on How to Do Well in this Course? Click here
Did you miss my Tips on what kind of calculator you should get? Click here
Did you miss my Tips for Assignment 2? Click here
If you are taking the course by classroom lecture (Sections A01, A02, etc.), click here for my tips for your Assignment 3.
Tips for Assignment 3 (Sections A01, A02, etc.)
Tips will be sent once Assignment 3 is posted.
Study Lesson 4 in my study book (Density
Curves and the Normal Distribution; in older editions of my book this is
Lesson 2) to learn the concepts involved in Assignment 3.
To learn this lesson and do this assignment, you need Table A
from the textbook. That can be downloaded from the Resources section
of Stats Portal. Here is a direct link to download this table:
Questions 1 and 2 are just like my
questions 5 and 6 in Lesson 4. Note, a "cumulative proportion" is a
left area on the bell curve. When they ask for the cumulative proportion, they are merely asking for the area to the left of the given z score. Put another way, cumulative proportion is
P(Z < z).
Question 3 is a good run through of X-bell curve problems that I teach in the latter half of Lesson 4. When they ask what score on the Reading Test is equivalent to Michael's Mathematics score, you will need to do some algebra. First, you can determine Michael's z score for math. Do not round that answer off, keep at lest four decimal places in your answer for the z score. Since the reading score is equivalent, you know that this must also be Michael's z score for reading. You can then use that z to work out the actual equivalent reading score.
Question 4
For the JMP part of the assignment, here are some tips:
Open a "New Data Table" in JMP. Click the link to the data they provide in the question. Press "Ctrl-A" to select all, or click and drag to select all the data. Press "Ctrl-C" to copy it or right-click and select "Copy". To paste the data into JMP, in the toolbar at top select "Edit" then "Paste
with Column Names". Double-click the "gpa" column heading and make
sure the Data Type is Numeric and the Modeling Type is Continuous, using
the drop-down menus to fix that if necessary. Double-click the "sex"
column heading and make sure the Data Type is Character and the Modeling
Type is Nominal, using the drop-down menus to fix that if necessary.
Click OK.
To get side-by-side boxplots: In the
toolbar at the top, select Analyze then select Fit Y By X. In the
pop-up menu, highlight the gpa column and click the "Y, Response"
button. Highlight the sex column and click the "X, Factor" button.
Click OK. You will then see a graph with a vertical array of dots for
the males (1) and the females (2). Click the red triangle next to
"Oneway Analysis ..." and select "Display Options". You will then be
able to select "Box Plots" in the Display Options sub-menu. They want
you to remove the Grand Mean line, so click the red triangle again and
select Display Options and deselect Grand Mean. Click the red triangle again and select Display Options and deselect "Show Points" to remove the points, but don't do that until you have used the points to help you identify the outliers they ask about in part (b).
You will need to copy and paste this output into a document
to get ready to add the output from part (b) as well. Here is how to do
that:
Press "Alt" or click the thin blue line near the top of the window that has
the boxplots to reveal the toolbar. Select the icon that looks
like a fat white cross or plus sign "+". This is your "Selection"
tool. Your mouse cursor should now have changed from an arrow to that
white cross. Click the title bar that says "Oneway Analysis ..." at the top
of the output and that should select the entire output (boxplots, etc.). Right-click and select Copy.
Now, open whatever program you use for word processing (such
as Word). In a new document, right-click and select Paste to paste your
output into the document.
They also ask you to comment on the graphs. I suggest you do
this by adding a note to the document you have just pasted the output
into. Just type your comments below all the JMP stuff. Compare the shape, centre and spread of the two boxplots.
Leave this document open, as you will need to paste the stuff from part (b) into it as well.
A normal quantile plot checks to see if a
sample's distribution appears to be normal. If the data follows a
normal distribution, the normal quantile plot will look like a rising
diagonal line. If the plot looks curved rather than linear, there is
evidence the data is not normal. However, none of that seems to matter
in your question, all they ask is which students are clear outliers,
which, personally, I think is much easier to see from the points in your side-by-side
boxplots than from your normal quantile plots.
Pretend you can see the outliers in the normal quantile plots, but really identify them from the boxplots above.
Press "Alt" or click the thin blue line near the top of the window that has
the normal quantile plots to reveal the toolbar. Select the icon that looks
like a fat white cross or plus sign "+". This is your "Selection"
tool. Your mouse cursor should now have changed from an arrow to that
white cross. You need to the graphs for both the females and males. Click the title bar that says "Distributions sex=.." to select one of either the females or males output. Right-click and select Copy. Paste it into the Word document you opened up in part (a). Now return to the JMP output and select the other output and copy and paste it into the Word document.
Write a short note underneath these graphs identifying which scores are outliers. You know very little according to the data table, so I suggest you just tell them the actual GPA you consider an outlier (there may be more than one), and if it is a male or female that has that GPA. To assist you in identifying the actual GPA scores, you can sort the data table in order of ascending GPA. To do so, in the data table, select "Tables" in the toolbar at top, and select "Sort". In the "Sort-JMP" pop-up window, select "GPA" and click "By" and click OK. You will then be shown a new data table with the data sorted in order of ascending GPA. You can now easily read off the smallest and largest GPAs and list the ones you consider outliers according to the side-by-side boxplots you made in part (a).
You can now save this Word file as a PDF and upload it into your assignment.