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TU S
Statistics for Managers
VI U
Using Microsoft Excel
T
A_V
9th Edition
MIA
SOLUTIONS
E_DA
MANUAL
CPO
PNR
David M. Levine David F. Stephan Kathryn A. Szabat
NOO
Comprehensive Solutions Manual for Instructors and Students
VIESS
||| ||| || ||| || | || ||| | || ||| |
9780135969854
DE?U
© David M. Levine, David F. Stephan & Kathryn A. Szabat. All rights reserved.
Reproduction or distribution without permission is prohibited.
R?
© MEDGEEK
,TU S
TABLE OF CONTENTS
Solutions Manual – Statistics for Managers Using Microsoft Excel (9th Edition)
Authors: David M. Levine, David F. Stephan, and Kathryn A. Szabat
ISBN: 9780135969854
VI U
PART I: INTRODUCTION AND DESCRIPTIVE STATISTICS
T
Chapter 1: Defining and Collecting Data
A_V
Chapter 2: Organizing and Visualizing Variables
Chapter 3: Numerical Descriptive Measures
PART II: PROBABILITY AND CONTINUOUS DISTRIBUTIONS
MIA
Chapter 4: Basic Probability
Chapter 5: Discrete Probability Distributions
Chapter 6: The Normal Distribution and Other Continuous Distributions
E_DA
PART III: STATISTICAL INFERENCE
Chapter 7: Sampling Distributions
Chapter 8: Confidence Interval Estimation
Chapter 9: Fundamentals of Hypothesis Testing: One-Sample Tests
CPO
Chapter 10: Two-Sample Tests
Chapter 11: Analysis of Variance
Chapter 12: Chi-Square and Nonparametric Tests
PNR
PART IV: REGRESSION ANALYSIS AND FORECASTING
Chapter 13: Simple Linear Regression
Chapter 14: Introduction to Multiple Regression
NOO
Chapter 15: Multiple Regression Model Building
Chapter 16: Time-Series Forecasting
PART V: ANALYTICS AND OPERATIONAL TOPICS
VIESS
Chapter 17: Business Analytics
Chapter 18: Getting Ready to Analyze Data in the Future
Chapter 19: Statistical Applications in Quality Management
Chapter 20: Decision Making
DE?U
R?
,TU S
Chapter 1
1.1 (a) The type of beverage sold yields categorical or “qualitative” responses rather than
numerical responses. Each beverage type represents a separate category.
(b) The type of beverage category expresses no order or ranking.
VI U
1.2 Business size represents a categorical variable because each size represents a particular category.
Because of the different sizes, order is implied, but this variable includes no information about
T
the quantity of differences among the three sizes.
A_V
1.3 (a) The time it takes to download a video from the Internet is a continuous numerical or
“quantitative” variable because time can have any value from 0 to any reasonable unit of
time
(b) The time it takes to download a video from the Internet is a ratio-scaled variable because
it is an ordered scale that includes a true zero point.
MIA
1.4 (a) The number of cellphones is a numerical variable that is discrete because the outcome is
a count.
(b) Monthly data usage is a numerical variable that is continuous because any value within a
E_DA
range of values can occur.
(c) Number of text messages exchanged per month is a numerical variable that is discrete
because the outcome is a count.
(d) Voice usage per month is a numerical variable that is continuous because any value
within a range of values can occur.
(e) Whether a cellphone is used for streaming video is a categorical variable because the
CPO
answer can be only yes or no.
1.5 (a) numerical, ratio
(b) numerical, ratio
PNR
(c) categorical, nominal
(d) categorical, nominal
1.6 (a) Categorical, nominal scale
(b) Numerical, continuous, ratio scale
NOO
(c) Categorical, nominal scale
(d) Numerical, discrete, ratio scale
(e) Categorical, nominal scale
VIESS
1.7 (a) numerical, ratio scale, continuous
(b) categorical, nominal scale
(c) categorical, nominal scale
(d) numerical, ratio scale, discrete
1.8 (a) numerical, continuous, ratio scale
DE?U
(b) numerical, discrete, ratio scale
(c) numerical, continuous, ratio scale
(d) categorical, nominal scale
R?
, 40 Chapter 1: Defining and Collecting Data
TU S
1.9 (a) Income may be considered discrete if we “count” our money. It may be considered
continuous if we “measure” our money; we are only limited by the way a country's
monetary system treats its currency.
(b) The first format would provide more information because it includes a ratio scale value
while the second measure would only include a range of values for each choice category.
VI U
1.10 The underlying variable, ability of the students, may be continuous, but the measuring device, the
test, does not have enough precision to distinguish between the two students.
T
1.11 (a) The population is “all working women from the metropolitan area.” A systematic or
A_V
random sample could be taken of women from the metropolitan area. The director might
wish to collect both numerical and categorical data.
(b) Three categorical questions might be occupation, marital status, type of clothing.
Numerical questions might be age, average monthly hours shopping for clothing, income.
MIA
1.12 (a) Data distributed by an organization or individual.
(b) The American Community Survey is based on a sample.
1.13 The answer depends on the specific story.
E_DA
1.14 The answer depends on the specific story.
1.15 The transportation engineers and planners should use primary data collected through an
observational study of the driving characteristics of drivers over the course of a month.
CPO
1.16 The information presented there is based mainly on a mixture of data distributed by an
organization and data collected by ongoing business activities.
1.17 (a) 001
(b) 040
PNR
(c) 902
1.18 Sample without replacement: Read from left to right in 3-digit sequences and continue unfinished
sequences from end of row to beginning of next row.
NOO
Row 05: 338 505 855 551 438 855 077 186 579 488 767 833 170
Rows 05–06: 897
Row 06: 340 033 648 847 204 334 639 193 639 411 095 924
Rows 06–07: 707
Row 07: 054 329 776 100 871 007 255 980 646 886 823 920 461
VIESS
Row 08: 893 829 380 900 796 959 453 410 181 277 660 908 887
Rows 08–09: 237
Row 09: 818 721 426 714 050 785 223 801 670 353 362 449
Rows 09–10: 406
Note: All sequences above 902 and duplicates are discarded.
DE?U
1.19 (a) Row 29: 12 47 83 76 22 99 65 93 10 65 83 61 36 98 89 58 86 92 71
Note: All sequences above 93 and all repeating sequences are discarded.
(b) Row 29: 12 47 83 76 22 99 65 93 10 65 83 61 36 98 89 58 86
Note: All sequences above 93 are discarded. Elements 65 and 83 are repeated.
R?
Copyright ©2021 Pearson Education, Inc.
TU S
Statistics for Managers
VI U
Using Microsoft Excel
T
A_V
9th Edition
MIA
SOLUTIONS
E_DA
MANUAL
CPO
PNR
David M. Levine David F. Stephan Kathryn A. Szabat
NOO
Comprehensive Solutions Manual for Instructors and Students
VIESS
||| ||| || ||| || | || ||| | || ||| |
9780135969854
DE?U
© David M. Levine, David F. Stephan & Kathryn A. Szabat. All rights reserved.
Reproduction or distribution without permission is prohibited.
R?
© MEDGEEK
,TU S
TABLE OF CONTENTS
Solutions Manual – Statistics for Managers Using Microsoft Excel (9th Edition)
Authors: David M. Levine, David F. Stephan, and Kathryn A. Szabat
ISBN: 9780135969854
VI U
PART I: INTRODUCTION AND DESCRIPTIVE STATISTICS
T
Chapter 1: Defining and Collecting Data
A_V
Chapter 2: Organizing and Visualizing Variables
Chapter 3: Numerical Descriptive Measures
PART II: PROBABILITY AND CONTINUOUS DISTRIBUTIONS
MIA
Chapter 4: Basic Probability
Chapter 5: Discrete Probability Distributions
Chapter 6: The Normal Distribution and Other Continuous Distributions
E_DA
PART III: STATISTICAL INFERENCE
Chapter 7: Sampling Distributions
Chapter 8: Confidence Interval Estimation
Chapter 9: Fundamentals of Hypothesis Testing: One-Sample Tests
CPO
Chapter 10: Two-Sample Tests
Chapter 11: Analysis of Variance
Chapter 12: Chi-Square and Nonparametric Tests
PNR
PART IV: REGRESSION ANALYSIS AND FORECASTING
Chapter 13: Simple Linear Regression
Chapter 14: Introduction to Multiple Regression
NOO
Chapter 15: Multiple Regression Model Building
Chapter 16: Time-Series Forecasting
PART V: ANALYTICS AND OPERATIONAL TOPICS
VIESS
Chapter 17: Business Analytics
Chapter 18: Getting Ready to Analyze Data in the Future
Chapter 19: Statistical Applications in Quality Management
Chapter 20: Decision Making
DE?U
R?
,TU S
Chapter 1
1.1 (a) The type of beverage sold yields categorical or “qualitative” responses rather than
numerical responses. Each beverage type represents a separate category.
(b) The type of beverage category expresses no order or ranking.
VI U
1.2 Business size represents a categorical variable because each size represents a particular category.
Because of the different sizes, order is implied, but this variable includes no information about
T
the quantity of differences among the three sizes.
A_V
1.3 (a) The time it takes to download a video from the Internet is a continuous numerical or
“quantitative” variable because time can have any value from 0 to any reasonable unit of
time
(b) The time it takes to download a video from the Internet is a ratio-scaled variable because
it is an ordered scale that includes a true zero point.
MIA
1.4 (a) The number of cellphones is a numerical variable that is discrete because the outcome is
a count.
(b) Monthly data usage is a numerical variable that is continuous because any value within a
E_DA
range of values can occur.
(c) Number of text messages exchanged per month is a numerical variable that is discrete
because the outcome is a count.
(d) Voice usage per month is a numerical variable that is continuous because any value
within a range of values can occur.
(e) Whether a cellphone is used for streaming video is a categorical variable because the
CPO
answer can be only yes or no.
1.5 (a) numerical, ratio
(b) numerical, ratio
PNR
(c) categorical, nominal
(d) categorical, nominal
1.6 (a) Categorical, nominal scale
(b) Numerical, continuous, ratio scale
NOO
(c) Categorical, nominal scale
(d) Numerical, discrete, ratio scale
(e) Categorical, nominal scale
VIESS
1.7 (a) numerical, ratio scale, continuous
(b) categorical, nominal scale
(c) categorical, nominal scale
(d) numerical, ratio scale, discrete
1.8 (a) numerical, continuous, ratio scale
DE?U
(b) numerical, discrete, ratio scale
(c) numerical, continuous, ratio scale
(d) categorical, nominal scale
R?
, 40 Chapter 1: Defining and Collecting Data
TU S
1.9 (a) Income may be considered discrete if we “count” our money. It may be considered
continuous if we “measure” our money; we are only limited by the way a country's
monetary system treats its currency.
(b) The first format would provide more information because it includes a ratio scale value
while the second measure would only include a range of values for each choice category.
VI U
1.10 The underlying variable, ability of the students, may be continuous, but the measuring device, the
test, does not have enough precision to distinguish between the two students.
T
1.11 (a) The population is “all working women from the metropolitan area.” A systematic or
A_V
random sample could be taken of women from the metropolitan area. The director might
wish to collect both numerical and categorical data.
(b) Three categorical questions might be occupation, marital status, type of clothing.
Numerical questions might be age, average monthly hours shopping for clothing, income.
MIA
1.12 (a) Data distributed by an organization or individual.
(b) The American Community Survey is based on a sample.
1.13 The answer depends on the specific story.
E_DA
1.14 The answer depends on the specific story.
1.15 The transportation engineers and planners should use primary data collected through an
observational study of the driving characteristics of drivers over the course of a month.
CPO
1.16 The information presented there is based mainly on a mixture of data distributed by an
organization and data collected by ongoing business activities.
1.17 (a) 001
(b) 040
PNR
(c) 902
1.18 Sample without replacement: Read from left to right in 3-digit sequences and continue unfinished
sequences from end of row to beginning of next row.
NOO
Row 05: 338 505 855 551 438 855 077 186 579 488 767 833 170
Rows 05–06: 897
Row 06: 340 033 648 847 204 334 639 193 639 411 095 924
Rows 06–07: 707
Row 07: 054 329 776 100 871 007 255 980 646 886 823 920 461
VIESS
Row 08: 893 829 380 900 796 959 453 410 181 277 660 908 887
Rows 08–09: 237
Row 09: 818 721 426 714 050 785 223 801 670 353 362 449
Rows 09–10: 406
Note: All sequences above 902 and duplicates are discarded.
DE?U
1.19 (a) Row 29: 12 47 83 76 22 99 65 93 10 65 83 61 36 98 89 58 86 92 71
Note: All sequences above 93 and all repeating sequences are discarded.
(b) Row 29: 12 47 83 76 22 99 65 93 10 65 83 61 36 98 89 58 86
Note: All sequences above 93 are discarded. Elements 65 and 83 are repeated.
R?
Copyright ©2021 Pearson Education, Inc.
