Stat 2000: Tips for Assignment 5
Published: Fri, 11/18/11
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If you are taking the course by classroom lecture (Sections A01, A02, etc.), click here for my tips for your Assignment 5.
You need to study the Chi-Square Goodness of Fit part of Lesson 8: Chi-Square Tests (if you are using an older edition of my book, this may be Lesson 9). You also will need to study Lesson 9: Review of Linear Regression and Lesson 10: Inferences for Linear Regression (up to the end of question 3, you do not need to study the Multiple Linear Regression section at this time).
Question 1 is not unlike my question 5 in Lesson 8.
Question 2 not unlike my questions 8 and 9 in Lesson 8.
Question 3 is not unlike my questions 10 and 11 in Lesson 8.
Question 4 is a runthrough of Linear Regression. Be sure to study Lessons 9 and 10 in my book before attempting this and the rest of the questions in this assignment. You should especially work through question 1 in Lesson 9 and questions 1 and 3 in Lesson 10.
To do Linear Regression in JMP:
Open a "New Data Table". Double-click Column 1 and name it "Marijuana Use" and click OK. Type in all the Marijuana Use data into that column. Double-click the region to the right of column 1 to create Column 2 and name it "Other Drug Use" and enter all its data. Select "Analyze, Fit Y By X". Highlight "Marijuana Use" and click "X, Factor". Highlight "Other Drug Use" and click "Y, Response". Click OK.
You should now be looking at a scatterplot. Click the red triangle and select "Fit Line" to get the least-squares regression line. You now have all the outputs you need. Note that JMP gives you the coefficient of determination, r2, which you can use to determine r. Be careful to assign the correct sign to r. Be sure to read in Lesson 10 the connection between the t test statistic for the slope and the t test statistic for the correlation. It is not clear in the question, but perhaps they want you to do the hypothesis in part (c) by hand (even though JMP does do it for you and give you the P-value).
I show you how to make predictions and compute residuals in Lesson 9. When they ask what does the sign of the residual tell you, they just want you to discuss whether the actual result is higher or lower than predicted.
Part (f) is tricky. Think of the ramifications of your conclusion in part (c). Are they also asking you does x cause y?
Question 5 requires the use of JMP.
Open a "New Data Table" and create two columns. Name the first column
"Temperature" and the second column "Sales". Remember, to create a new
column, simply double-click in the space at the top of the column, to
the right of a pre-existing column. Enter in the data manually, and we
are now ready to analyze the data. Double-click both column names and
confirm their Data Type is Numeric and their Modeling Type is
Continuous.
Question 5(a) wants you to list the model. No numbers. I show you how to write the model in Lesson 10. Be sure to use the symbols β0 and β1 rather than α and β to tie in with the symbols they use later in the question.
Question 5(b):
Select "Analyze" then "Fit Y by X". You should be able to tell which
is x and which is y. Select the y variable and click "Y, Response" and
select the x variable and click "X, Factor". Click OK. You will now
see a scatterplot. Click the red triangle next to "Bivariate Fit ..."
and select "Fit Line" to have JMP compute and graph the least-squares
regression line.
Question 5(c): Click the red triangle next to Linear Fit and select Residual Plot to get the graph of the residuals.
Question 5(d): JMP gives you this estimate in the Summary of Fit. But it sounds like they want you to compute the standard deviation of the residuals by hand (as I show in question 1(k) in Lesson 9. This isn't hard to do at all since you are given the sum of the squared residuals.
Question 5(e) and (f): These must be computed by hand using
the appropriate formulas and numbers from JMP as I show in my question 3
of Lesson 10. Note that you have been given some useful numbers in that regard at the start of this question.
Question 5(g) and (h): Click the red triangle next to "Linear Fit" and select "Confid Curve
Indiv" and "Confid Curve Fit" to get these two intervals they want. As I
tell you in Lesson 10, the curves that are closer to the line are the
confidence intervals for the mean, the outer curves are the prediction
intervals. It sounds like they want you to print the JMP output without these curves drawn in, and then print it again with the curves.
Question 5(i):
JMP already did this test for you when you selected "Fit Line". The
ANOVA table and the "Parameter Estimates" are giving you all the
info you need, but be sure to write out your hypotheses and conclusion
in the file you are uploading. However, they want you to do it by hand. This isn't so bad because of the values you have already computed in part (d) and the givens at the start of the problem.
Question 5(n): You
should know what this ratio they want here and how to determine it. I
talk about this in Lesson 10, and show you how to interpret it in
question 1 of Lesson 9.
There is no distance/online course for Stat 2000 this term.