Statistics for Business and Economics (13th Edition)
13th Edition
ISBN: 9780134506593
Author: James T. McClave, P. George Benson, Terry Sincich
Publisher: PEARSON
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Textbook Question
Chapter 11.3, Problem 11.42ACI
Sweetness of orange juice. Refer to the study of the quality of orange juice produced at a juice manufacturing plant, Exercise 11.26 (p. 632). Recall that simple linear regression was used to predict the sweetness index (y) from the amount of pectin (x) in the orange juice.
a. Find the values of SSE, s2, and s for this regression.
b. Explain why it is difficult to give a practical interpretation to s2.
c. Give a practical interpretation of the value of s.
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A group of students measure the length and width of a random sample of beans. They are interested in investigating the relationship between the length and width. Their summary statistics are displayed in the table below. All units, if applicable, are millimeters.
Mean width:
7.555
Stdev width:
0.914
Mean height:
12.686
Stdev height:
1.634
Correlation coefficient:
0.8203
d) If the students are interested in using the height of the beans to predict the width, calculate the slope of this new regression equation.
e) Write the equation of the best-fit line that can be used to predict bean widths. Use x to represent height and y to represent width.
(a) The standard error Se of the linear regression model is given in the printout as "S." What is the value of Se?
The U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below.
Table 7: Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.854a
.730
.695
6.6235
a. Predictors: (Constant), Hourly Wage
Table 8: ANOVA
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
1918.458
1
1918.458
129.783
.000a
Residual
709.567
48
14.782
Total
2628.025
49
a. Predictors: (Constant), Hourly Wage
b. Dependent Variable: Number of Complaints
Table 9: Coefficients
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t…
Chapter 11 Solutions
Statistics for Business and Economics (13th Edition)
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