Stat 2000: Tips for Web Assign HW 05
Published: Thu, 02/17/11
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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 05.
Study Lesson 6 in my study book to prepare for this assignment. Those of you with an older edition will study Lessons 6 and 7 (and really only study about the first two questions of Lesson 6, then move on to Lesson 7: The Binomial and Poisson Distributions).
Question 1 is just like my questions 1, 2 and 3. I show you the formulas for the mean and standard deviation required.
Question 2 is dealing with the properties of mean and variance I taught back in Lesson 4 of my book. Take a look at the first couple of questions I do in Lesson 4.
The rest of the assignment is all standard Binomial and Poisson distribution questions.
Study Lesson 5 in my study book to prepare for this assignment.
For Question 1, note that ni simply means they want you to tell them the values of n1, n2, etc..
For Question 2, you should certainly use the stat mode in your calculator to compute the means and standard deviations (which will, of course, enable you to know the variances), then do the rest of the problem by hand using the formulas for SSG, SSE, MSG, MSE, and F. Make sure you have memorized those formulas (and the formula for the overall mean or grand mean). There is almost certainly going to be a question or two on the exam that will check to see if you know these formulas (although it is rare to see an exam question that makes you do an entire ANOVA by hand). It is common that an exam will make you compute MSG or MSE by hand having been given the sample means and standard deviations. Note, throughout the question they tell you to do "second - first", so make sure you do. That makes their hypotheses confusing. I assume they mean by μ1 the mean of the first coinage, but, then again, it doesn't really matter.
Here is how to do the JMP part of Question 3:
It is done the same way you did the JMP in the previous assignment. Open a New Data Table and type the data in manually in this manner (don't bother pasting and stacking, it is not worth the effort): Name your first column "Silver" or something like that, and type all the silver contents down that column. Which is to say, type in the numbers from the First coinage down the column, then continue to type all the numbers from the Second coinage, and finally continue to type all the numbers for the Third coinage. Double-click at the top to the right of the "Silver" column heading to create a new column and name it something like "Coinage". Down that column type "First" repeatedly down that column in all the rows that have the data for the First coinage. Then type "Second" repeatedly down the column in the rows that have data for the Second coinage. Finally, type "Third" for the rest of the column. You may want to type the phrase once and then copy and paste it down the rest of the relevant rows to ensure there are no typos. Once you have done that, double-click the "Coinage" column heading and confirm that the Data Type is Character and the Modeling Type is Nominal and click OK.
Select Analyze, then Fit Y By X. Highlight the numeric column "Silver" and click the Y, Response button. Highlight the character column "Coinage" and click the X, Factor button. Click OK.
You should now see a graph with three vertical arrays of dots showing the silver content for the three different coinages separately. Click the red triangle and select "Means and Std Dev" to get a summary of the means and standard deviations of the three samples. Click the red triangle again and select "Means/Anova/Pooled t" to get the output you need.
By the way, be sure to study my questions 5 and 6 in Lesson 5 thoroughly to better understand what they are getting at in part (d).
In Question 4 the applet is pretty straightforward to learn from. Note that the pooled standard error is essentially MSE. Remember, F = MSG/MSE and think about what affects the value of MSG and MSE and how those two values affect the value of F. The applet pretty well teaches you what happens. Messing with one part changes MSG, messing with the other part changes MSE.
Do the JMP in Question 5 just like I showed you what to do in Question 3 above. Here at least you can copy and paste the data into JMP. Be sure to paste it into JMP by selecting Edit, then, while holding down the Shift key, select Paste in order to paste the column headings properly (or, after you have copied the data, select "Edit" then "Paste with Column Names"). Note, double-click the "bfed" column and confirm that its Data Type is Character and Modeling Type is Nominal; double-click the "energy" column and confirm that its Data Type is Numeric and Modeling Type is Continuous. Always make the numeric column Y and the character column X when you select Fit Y By X.
Re-read my section on the P-value in Lesson 2 of my book if you still are not sure how to interpret a P-value.