Solutions for Essentials of Modern Business Statistics with Microsoft® Excel®, 9th Edition by Camm (All Chapters included)
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Introduction to Statistics
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Introduction To Statistics
Complete Solutions Manual for Essentials of Modern Business Statistics with Microsoft® Excel®, 9th Edition by Jeffrey D. Camm ; ISBN13: 9780357930045.....(Full Chapters included and organized in reverse order from Chapter 15 to 1)...1. Data and Statistics.
2. Descriptive Statistics: Tabular and ...
Essentials of Modern Business
Statistics with Microsoft® Excel®,
9th Edition by Jeffrey D. Camm
Complete Chapter Solutions Manual
are included (Ch 1 to 15)
** Immediate Download
** Swift Response
** All Chapters included
** Appendix Solutions
,Table of Contents are given below
1. Data and Statistics.
2. Descriptive Statistics: Tabular and Graphical Displays.
3. Descriptive Statistics: Numerical Measures.
4. Introduction to Probability.
5. Discrete Probability Distributions.
6. Continuous Probability Distributions.
7. Sampling and Sampling Distributions.
8. Interval Estimation.
9. Hypothesis Tests.
10. Inferences About Means and Proportions with Two Populations.
11. Inferences About Population Variances.
12. Test of Goodness of Fit, Independence, and Multiple Proportions.
13. Experimental Design and Analysis of Variance.
14. Simple Linear Regression.
15. Multiple Regression.
,Solutions Manual organized in reverse order, with the last chapter displayed
first, to ensure that all chapters are included in this document.
(Complete Chapters included Ch15-1)
Solution and Answer Guide
CAMM/COCHRAN/FRY/OHLMANN/ANDERSON/SWEENEY/WILLIAMS, ESSENTIALS OF MODERN
BUSINESS STATISTICS W/MS EXCEL 9TH EDITION, 9780357984505;
CHAPTER 15: MULTIPLE REGRESSION
TABLE OF CONTENTS
Exercises ...................................................................................................................................................... 1
Supplementary Exercises ......................................................................................................................... 49
Case problem 1: consumer research, inc. ............................................................................................... 73
Case Problem 2: Predicting Winnings For Nascar Drivers .................................................................. 77
Case Problem 3: Finding the Best Car Value ......................................................................................... 82
EXERCISES
Methods
1. The estimated regression equation for a model involving two independent variables and 10 observations
follows. LO 2, 3
ŷ = 29.1270 + 0.5906x1 + 0.4980x2
a. Interpret b1 and b2 in this estimated regression equation.
b. Predict y when x1 = 180 and x2 = 310.
Solutions:
a. b1 = 0.5906 is an estimate of the change in y corresponding to a one-unit change in x1 when x2 is held
constant.
b2 = 0.4980 is an estimate of the change in y corresponding to a one-unit change in x2 when x1 is held
constant.
b. ŷ = 29.1270 + 5,906(180) + 0.4980(310) = 289.815
2. Consider the following data for a dependent variable y and two independent variables, x1 and x2. LO 1, 3
x1 x2 y
30 12 94
47 10 108
25 17 112
51 16 178
40 5 94
51 19 175
74 7 170
36 12 117
59 13 142
76 16 211
1
, a. Develop an estimated regression equation relating y to x1. Predict y if x1 = 45.
b. Develop an estimated regression equation relating y to x2. Predict y if x2 = 15.
c. Develop an estimated regression equation relating y to x1 and x2. Predict y if
x1 = 45 and x2 = 15.
Solutions:
a. Using the file exertwo and Excel’s Descriptive Statistics Regression Tool, the Excel output is shown
below:
Regression Statistics
Multiple R 0.8124
R Square 0.6600
Adjusted R Square 0.6175
Standard Error 25.4009
Observations 10
ANOVA
df SS MS F Significance F
Regression 1 10021.24739 10021.25 15.5318 0.0043
Residual 8 5161.652607 645.2066
Total 9 15182.9
Coefficients Standard Error t Stat p-Value
Intercept 45.0594 25.4181 1.7727 0.1142
X1 1.9436 0.4932 3.9410 0.0043
An estimate of y when x1 = 45 is
ŷ = 45.0594 + 1.9436(45) = 132.52
b. Using the file exertwo and Excel’s Descriptive Statistics Regression Tool, the Excel output is shown
below:
Regression Statistics
Multiple R 0.4707
R Square 0.2215
Adjusted R Square 0.1242
Standard Error 38.4374
Observations 10
ANOVA
df SS MS F Significance F
Regression 1 3363.4142 3363.414 2.2765 0.1698
Residual 8 11819.4858 1477.436
Total 9 15182.9
2
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