Example 1 Processing Time vs. Lot Size for the Toluca Company
www.oswego.edu/~srp/stats/toluca.txt
The first column is the shipment size (in lots), the second is the time (manhours) it takes to
process the shipment.
1. Produce a fitted line plot.
2. Identify and interpret.
Explanatory variable
Response
Fitted regression line
Equation:
_______________________
Slope
Intercept
Coefficient of variation
Value: ________
Value: ________
Value: ________
Meaning:
Meaning:
Meaning:
Correlation coefficient
Standard deviation
Value: ________
Value: ________
Meaning:
3. Determine the predicted time of process a shipment of 50 lots.
__________
4. There are three shipments of 50 lots in the data set. For each, determine the residual.
__________
__________
__________
5. Perform a regression analysis. Use the Storage button to store the fits and residuals. Examine
the worksheet to check on your results to 3 and 4.
6. Determine the predicted time for a shipment of 95 lots.
__________
7. Examine a histogram of the residuals. Check this in terms of the known mean of 0 and the
standard deviation from your regression analysis. Would you say they are nearly normally
distributed? Why (not)?
Regression Worksheet
1
Example 2 Book Length and Price
www.oswego.edu/~srp/stats/ProfBooks.txt
For each of 15 books, the number of pages and the price is given. Some are hardcover (H); some
are softcover (S).
1. Produce a fitted line plot.
2. Identify and interpret.
Explanatory variable
Response
Fitted regression line
Equation:
_______________________
Slope
Intercept
Coefficient of variation
Value: ________
Value: ________
Value: ________
Meaning:
Meaning:
Meaning:
Correlation coefficient
Standard deviation
Value: ________
Value: ________
Meaning:
The line does not fit very well. It would appear there is if anything a negative association
between the two variables. Why? How could more pages result in lower price?
Regression Worksheet
2
Example 3 Muscle Mass vs. Woman’s Age
www.oswego.edu/~srp/stats/mmass.txt
Here we predict a woman’s muscle mass (g/cc) on the basis of her age (yrs).
1. Produce a fitted line plot.
2. Identify and interpret.
Explanatory variable
Response
Fitted regression line
Equation:
_______________________
Slope
Intercept
Coefficient of variation
Value: ________
Value: ________
Value: ________
Meaning:
Meaning:
Meaning:
Correlation coefficient
Standard deviation
Value: ________
Value: ________
Meaning:
3. Predict muscle mass for a 60 year-old woman. (No 60 year old women are in the data set, yet
we can still use the line to do this.)
Regression Worksheet
3
Homework
Example 2 Book Length and Price
www.oswego.edu/~srp/stats/ProfBooks.txt
1. Reproduce the fitted line plot and store the residuals. Note the value of R2.
__________
2. How many of the hardcover books have positive residuals? Negative? How about the
softcover books? What does this tell you about the scatterplot and fitted line?
You perhaps could have noticed something odd due to the type (hard vs. softcover) of book. You
would have for sure if you’d obtained the proper plot – a symbol plot. Produce a symbol plot of
Price (Y) vs. Pages (X) with symbols for each type of book. (This plot is duplicated at bottom.)
3. Using cut, copy and paste, isolate only the hardcover books.
4. Perform a regression analysis. Note the value of R2.
__________
5. Using cut, copy and paste, isolate only the softcover books.
6. Perform a regression analysis. Note the value of R2.
__________
2
7. Explain the discrepancy between the three (#1, #4, #6) values of R .
8. Carefully plot all three lines (#1, #4 and #6) on the scatterplot. Use a dotted line for #1.
H
S
80
70
60
Price
50
40
30
20
10
0
100
200
300
400
500
600
Pages
Regression Worksheet
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Example 3 Muscle Mass and Age
www.oswego.edu/~srp/stats/mmass.txt
1. Reproduce the fitted line plot and store the residuals.
2. Obtain a normal probability plot of the residuals. What information does this plot supply?
3. Obtain a scatterplot of the residuals (Y-axis) vs. age. This plot shows no apparent pattern.
4. Have Minitab produce the predicted value for muscle mass when age = 60. Do this by
running a regression analysis. Choose Options, and in the box for “Prediction intervals for
new observations” place the value 60. You will see the result of this input at the very bottom
of the Minitab output.
Regression Worksheet
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Regression Worksheet
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