Stat 2000: Tips for Assignment 5

Published: Fri, 11/30/12


 
My revised tips for Assignment 5 are coming below, but first a couple of announcements.
 
Please note that my final exam prep seminar for Stat 2000 will be on Sunday, Dec. 2, in room 100 St. Paul's College, from 9 am to 9 pm .  For complete info about the seminar, and to register if you have not done so already, click this link:
Stat 2000 Seminar 
 
I am also offering seminars in Calculus, Linear Algebra, and Stat 1000 in the coming weeks.  You can get info about those seminars here:
Grant's One-Day Exam Prep Seminars
 
If you ever want to look back over a previous tip I have sent, do note that all my tips can be found in my archive.  Click this link to go straight to my archive: 
Grant's Homework Help Archive
 
Make sure you have read my Tips on How to Do Well in this Course
 
Did you miss my Tips on what kind of calculator you should get? Click here
 
Did you miss my tips for Assignment 3? Click here
 
Tips for 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).  Note that they have omitted Multiple Linear Regression and Lesson 11: Nonparametric Tests (The Sign Test) this term.
 
Question 1 is not unlike my question 5 in Lesson 8.  Make sure you follow their instructions for rounding.  They make their goodness-of-fit table horizontally, while I prefer to make mine vertically.
 
Question 2 is not unlike my question 8 in Lesson 8.
 
Question 3 is not unlike my question 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.
 
Note that they give you SSE, the sum of the squared residuals, so you are able to compute the variance of the residuals (MSE = SSE/DFE).  MSE is your estimate for σ, as requested in part (e).  That is what I call se, the standard deviation of the residuals, the estimate for σε, the standard deviation of the population of residuals.
 
Never forget, in a regression context, if they start talking about σ or s, they are referring to the standard deviation of the residuals for the population or sample, respectively.  To add to the confusion, they called s, σ-hat in this part.
 
To do Linear Regression in JMP:
Open a "New Data Table".  Enter all the data for x in Column 1 and all the data for y in Column 2.  Be sure to name the columns appropriately.  I think you all get different questions here, so I am unable to be more specific.  Select "Analyze, Fit Y By X".  Highlight "Column 1" and click "X, Factor".  Highlight "Column 2" 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.  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.  And also the connection between t for the slope and F for the slope.  Although they want you to do a lot of this question by hand (and you certainly should since that will also happen on the exam), do note that JMP does do a lot of this stuff for you and you can use it to check your answers before you submit them.
 
Question 5 is not unlike my question 2 in Lesson 10.
 
Question 6 is not unlike my question 3 in Lesson 10.  Note that the proportion they ask for in part (c) is just the decimal version for a the relevant percentage.  As I show in my question 3, you can use the ANOVA to find that percentage or proportion.
 
Question 7 is probably the hardest question I have ever seen in a statistics assignment.