Stat 2000: Tips for Web Assign HW 07
Published: Fri, 03/18/11
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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 07.
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.
Question 1 is a standard goodness-of-fit problem.
Question 2 is playing with the concepts I discuss in question 4 of Lesson 8.
Question 3 is similar to my questions 10 and 11 in Lesson 8.
Question 4 is similar to my questions 8 and 9.
Continue to study Lesson 10 at least up to the end of question 3 to prepare for this assignment. You do not need to study the section on Multiple Linear Regression at this time. Note that HW 6, 7 and 8 all deal with concepts from Lesson 10.
Question 1 is similar to my question 3 in Lesson 10. Note, by s, the standard error points about the regression line, they mean the standard deviation of the residuals, se.
Question 2 is standard stuff. Obviously, watch that they have changed the value of n. This is demonstrating that, if you choose a large enough sample size, almost any nonzero r value will be statistically significant (but perhaps of no practical importance).
You will use JMP for question 3. Open a "New Data Table" and create two columns. Name the first column "Diameter" and the second column "Height". 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 3(a) and (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 3(c): JMP gives you the coefficient of determination, r2. Compute r from that value.
Question 3(d) and (e): 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.
Question 3(f): JMP already did this test for you when you selected "Fit Line". The ANOVA table and the "Parameter Estimates" for are giving you all the info you need, but be sure to write out your hypotheses and conclusion in the file you are uploading. You can determine if there is a linear relationship by either testing the hypothesis about zero correlation or a hypothesis about zero slope. JMP gives us the latter in the ANOVA and Parameter Estimates, so I would do the zero slope hypothesis. I show you how to read these outputs in my question 3 of Lesson 10.
Question 3(g) and (h): These must be computed by hand using the appropriate formulas and numbers from JMP as I show in my question 3 of Lesson 10.
Question 3(i): You should know what this ratio is computing 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.