Stat 1000: Tips for Assignment 10

Published: Fri, 03/16/12


I am still finalizing the date for the Final Exam Seminar for Stat 1000.  Please give me your input.  I am considering either Good Friday, April 6 or Saturday, April 7.
Please click this link for more information about the seminar if you are interested:
Grant's Stat 1000 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 Updates Archive
 
Did you miss my Tips on How to Do Well in this Course? Click here
 
Did you miss my Tips for Assignment 9? Click here
 
If you are taking the course by Distance/Online (Sections D01, D02, etc.), click here for my tips for your Assignment 10.
 
If you are taking the course by classroom lecture (Sections A01, A02, etc.), click here for my tips for your Assignment 10.
 
Tips for Assignment 10 (Sections A01, A02, etc.)
 
 There is no Assignment 10 for the classroom lecture sections.
 
Tips for Assignment 10 (Distance/Online Sections D01, D02, etc.)
 
Study Lesson 9: Hypothesis Tests for the Mean in my book, if you have it, to prepare for this topic.
 
You will be using Table A and Table D while learning Lesson 8 and doing this assignment.  Here is a link where you can download those tables if you have not done so already:
Table A
Table D
 
First, be sure to note whether a question gives you σ, the population standard deviation, or s, the sample standard deviation.  That dictates whether you will use z or t when testing your hypothesis.  I would assume, at this stage, you are likely to be given σ most of the time.
 
Question 1 is basic P-value stuff as taught in Lesson 9.  See my examples before question 6.
 
Questions 2 and 3 are a good run through of the 5 steps to test a hypothesis.
 
Question 4: Requires use of JMP.
 
To make a confidence interval for the mean using JMP:
Select and copy the data.  Click "New Data Table", then select "Edit" then "Paste with Column Names". Now select "Analyze", "Distribution" and highlight "radon" and click "Y, Columns", then click OK. You are now looking at a histogram and stuff. Click the red triangle next to "radon" then select "Confidence Interval" from the drop-down list. Select "Other" to get a pop-up menu. It probably already has 0.95 typed in (for 95% confidence interval), but, if not, be sure to type in 0.95. Make sure you click the box saying "Use known Sigma". Click "OK" and you will then get a pop-up menu to type in the sigma value. I believe σ = 9 in your case. Click "OK" and JMP gives you the Confidence Interval at the bottom of the printout.
 
To test a hypothesis for the mean using JMP:
You should already be in the output screen having done the confidence interval in part (a). You are now looking at a histogram and stuff. Click the red triangle next to the variable and select "Test Mean" from the drop-down list. Enter in the population mean as stated in your null hypothesis and enter in the given population standard deviation, sigma. Click "OK" and JMP gives you the hypothesis test at the bottom of the printout. Look at my questions 13 and 14 for examples of how to read this printout.
 
You can now select, copy and paste your output to a file ready for upload as usual.
 
Question 5:
Follow the same steps as done in question 4 to test the hypothesis about IQ.  Just make sure you make IQ your Y Column.
Make sure you read my section on P-values to learn how to properly interpret your P-value.
 
In question 6, remember the note I write after my question 4 talking about statistical significance versus practical significance. Also, remember the Law of Large Numbers taught in Lesson 7 of my book.  The key concept is, that as n, the sample size, gets larger, the sample mean will come closer and closer to the true mean, mu. Put another way, the larger the sample size, the closer your statistic will come to the TRUTH.  If the truth is that the null hypothesis is correct, then you are likely to get a larger and larger P-value, and so you would not be able to reject the null hypothesis.  However, if the truth is that the null hypothesis is wrong, then you would expect that larger and larger samples would more clearly prove that Ho is wrong, meaning you would get a smaller and smaller P-value, and stronger evidence to reject Ho.
 
Question 7 is just more practise at all the concepts.
http://grantstutoring.com/
http://www.facebook.com/grantstutoring
https://twitter.com/grantstutoring