Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams, Modern Business Statistics w/MS Excel 8th
Edition, 9780357929964; Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
Solution and Answer Guide
CAMM/COCHRAN/FRY/OHLMANN/ANDERSON/SWEENEY/WILLIAMS, MODERN BUSINESS
STATISTICS W/MS EXCEL 8TH EDITION, 9780357929964; CHAPTER 2: DESCRIPTIVE
STATISTICS: TABULAR AND GRAPHICAL DISPLAYS
TABLE OF CONTENTS
Practice Problems .................................................................................................................1
PRACTICE PROBLEMS
1. Top-Rated Television Show Networks. Nielsen Media Research tracks the top-rats
television shows. The following data show the television network that produced each
of the 25 top-rated shows in the history of television.
CBS CBS NBC FOX CBS
CBS NBC NBC NBC ABC
ABC NBC ABC ABC NBC
CBS NBC CBS ABC NBC
NBC CBS CBS ABC CBS
a. Construct a frequency distribution, percent frequency distribution, and bar chart
for the data.
b. Which networks have done the best in terms of presenting top-rated television
shows? Compare the performance of ABC, CBS, and NBC.
Solution:
Step 1. As outlined in the Appendix: Getting Started with R and RStudio, change the
working directory to where the file networks2012_r.csv is located
Step 2. To read the file and create a data frame, enter the following in the Console
pane of RStudio:
network_df = read.csv("networks2012_r.csv")
Step 3. Enter the following to create a table of tv networks and frequencies :
table(network_df)
The following table appears in the Console:
ABC CBS FOX NBC
6 9 1 9
© 2025 Cengage. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible 1
website, in whole or in part.
,Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams, Modern Business Statistics w/MS Excel 8th
Edition, 9780357929964; Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
Step 4. A similar function is used to construct a table of percent frequencies. Enter
the following:
prop.table(table(network_df))
The following table with network frequencies appears in the Console:
ABC CBS FOX NBC
0.24 0.36 0.04 0.36
Step 5. The following function will create a frequency chart from the table data.
barplot(table(network_df))
The following chart appears in the Plots pane of RStudio.
Step 6. The following command will create a frequency barplot.
barplot(prop.table(table(network_df)))
The following chart appears in the Plots pane of RStudio.
© 2025 Cengage. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible 2
website, in whole or in part.
,Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams, Modern Business Statistics w/MS Excel 8th
Edition, 9780357929964; Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
2. Low Temperatures and Snowfall. The file snow_r.csv contains temperature and snowfall
data for 51 major U.S. cities over 30 years. For example, the average low temperature for
Columbus, Ohio, is 44 degrees and the average annual snowfall is 27.5 inches.
a. Construct a scatter diagram with the average annual low temperature on the
horizontal axis and the average annual snowfall on the vertical axis.
b. Does there appear to be any relationship between these two variables?
c. Based on the scatter diagram, comment on any data points that seem to be unusual.
Solution:
a. Construct a scatter diagram with the average annual low temperature on the
horizontal axis and the average annual snowfall on the vertical axis.
Step 1. As outlined in the Appendix: Getting Started with R and RStudio, change
the working directory to where the file snow_r.csv is located
Step 2. To read the file and create a data frame, enter the following in the
Console pane of RStudio:
snow_df=read.csv("snow.csv")
Step3. The plot function is entered into the Console to produce the scatter plot.
Enter the following:
plot(snow_df$Temp,snow_df$Snowfall,main="Scatter Plot",xlab="Snowfall",
ylab="Temp",xlim=c(40,70),ylim=c(0,100))
The plot function follows this general form:
Plot(variable, main=”Title”, xlab=”x-axis label”, ylab=”y-axis label”,
xlim=c(lower x-axis, upper x-axis), ylim=c(lower y-axis, upper y-axis)
b. Does there appear to be any relationship between these two variables?
Colder average low temperature seems to lead to higher amounts of snowfall.
c. Based on the scatter diagram, comment on any data points that seem to be unusual.
Two cities have an average snowfall of nearly 100 inches of snowfall: Buffalo, New
York, and Rochester, New York. Both are located near large lakes in the state.
© 2025 Cengage. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible 3
website, in whole or in part.
, Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams, Modern Business Statistics w/MS Excel 8th
Edition, 9780357929964; Chapter 3: Descriptive Statistics: Numerical Measures
Solution and Answer Guide
CAMM/COCHRAN/FRY/OHLMANN/ANDERSON/SWEENEY/WILLIAMS, MODERN BUSINESS
STATISTICS W/MS EXCEL 8TH EDITION, 9780357929964; CHAPTER 3: DESCRIPTIVE
STATISTICS: NUMERICAL MEASURES
TABLE OF CONTENTS
Practice Problems .................................................................................................................1
PRACTICE PROBLEMS
1. eICU Waiting Time: There is a severe shortage of critical care doctors and nurses to
provide intensive-care services in hospitals. To offset this shortage, many hospitals,
such as Emory Hospital in Atlanta, are using electronic intensive-care units (eICUs) to
help provide this care to patients (Emory University News Center). eICUs use electronic
monitoring tools and two-way communication through video and audio so that a
centralized staff of specially trained doctors and nurses—who can be located as far
away as Australia—can provide critical care services to patients located in remote
hospitals without fully staffed ICUs. One of the most important metrics tracked by
these eICUs is the time that a patient must wait for the first video interaction between
the patient and the eICU staff. Consider the following sample of 40 patient waiting
times until their first video interaction with the eICU staff.
a. Compute the mean waiting time for these 40 patients.
b. Compare the median waiting time.
c. Compute the mode.
d. Compute the first and third quartiles.
Solution:
a. Compute the mean waiting time for these 40 patients.
Step 1. As outlined in the Appendix: Getting Started with R and RStudio, change
the working directory to where the file eicu_r.csv is located
Step 2. To read the file and create a data frame, enter the following in the
Console pane of RStudio:
eicu_df = read.csv("eicu_r.csv")
Step 3. A summary of the descriptive statistics for the Wait Time data is created
by entering the command:
summary(eicu_df)
In this case, there is no need to create a vector for the variable Wait.Time since it
is the only variable in the data frame.
© 2025 Cengage. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible 1
website, in whole or in part.
Edition, 9780357929964; Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
Solution and Answer Guide
CAMM/COCHRAN/FRY/OHLMANN/ANDERSON/SWEENEY/WILLIAMS, MODERN BUSINESS
STATISTICS W/MS EXCEL 8TH EDITION, 9780357929964; CHAPTER 2: DESCRIPTIVE
STATISTICS: TABULAR AND GRAPHICAL DISPLAYS
TABLE OF CONTENTS
Practice Problems .................................................................................................................1
PRACTICE PROBLEMS
1. Top-Rated Television Show Networks. Nielsen Media Research tracks the top-rats
television shows. The following data show the television network that produced each
of the 25 top-rated shows in the history of television.
CBS CBS NBC FOX CBS
CBS NBC NBC NBC ABC
ABC NBC ABC ABC NBC
CBS NBC CBS ABC NBC
NBC CBS CBS ABC CBS
a. Construct a frequency distribution, percent frequency distribution, and bar chart
for the data.
b. Which networks have done the best in terms of presenting top-rated television
shows? Compare the performance of ABC, CBS, and NBC.
Solution:
Step 1. As outlined in the Appendix: Getting Started with R and RStudio, change the
working directory to where the file networks2012_r.csv is located
Step 2. To read the file and create a data frame, enter the following in the Console
pane of RStudio:
network_df = read.csv("networks2012_r.csv")
Step 3. Enter the following to create a table of tv networks and frequencies :
table(network_df)
The following table appears in the Console:
ABC CBS FOX NBC
6 9 1 9
© 2025 Cengage. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible 1
website, in whole or in part.
,Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams, Modern Business Statistics w/MS Excel 8th
Edition, 9780357929964; Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
Step 4. A similar function is used to construct a table of percent frequencies. Enter
the following:
prop.table(table(network_df))
The following table with network frequencies appears in the Console:
ABC CBS FOX NBC
0.24 0.36 0.04 0.36
Step 5. The following function will create a frequency chart from the table data.
barplot(table(network_df))
The following chart appears in the Plots pane of RStudio.
Step 6. The following command will create a frequency barplot.
barplot(prop.table(table(network_df)))
The following chart appears in the Plots pane of RStudio.
© 2025 Cengage. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible 2
website, in whole or in part.
,Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams, Modern Business Statistics w/MS Excel 8th
Edition, 9780357929964; Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
2. Low Temperatures and Snowfall. The file snow_r.csv contains temperature and snowfall
data for 51 major U.S. cities over 30 years. For example, the average low temperature for
Columbus, Ohio, is 44 degrees and the average annual snowfall is 27.5 inches.
a. Construct a scatter diagram with the average annual low temperature on the
horizontal axis and the average annual snowfall on the vertical axis.
b. Does there appear to be any relationship between these two variables?
c. Based on the scatter diagram, comment on any data points that seem to be unusual.
Solution:
a. Construct a scatter diagram with the average annual low temperature on the
horizontal axis and the average annual snowfall on the vertical axis.
Step 1. As outlined in the Appendix: Getting Started with R and RStudio, change
the working directory to where the file snow_r.csv is located
Step 2. To read the file and create a data frame, enter the following in the
Console pane of RStudio:
snow_df=read.csv("snow.csv")
Step3. The plot function is entered into the Console to produce the scatter plot.
Enter the following:
plot(snow_df$Temp,snow_df$Snowfall,main="Scatter Plot",xlab="Snowfall",
ylab="Temp",xlim=c(40,70),ylim=c(0,100))
The plot function follows this general form:
Plot(variable, main=”Title”, xlab=”x-axis label”, ylab=”y-axis label”,
xlim=c(lower x-axis, upper x-axis), ylim=c(lower y-axis, upper y-axis)
b. Does there appear to be any relationship between these two variables?
Colder average low temperature seems to lead to higher amounts of snowfall.
c. Based on the scatter diagram, comment on any data points that seem to be unusual.
Two cities have an average snowfall of nearly 100 inches of snowfall: Buffalo, New
York, and Rochester, New York. Both are located near large lakes in the state.
© 2025 Cengage. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible 3
website, in whole or in part.
, Solution and Answer Guide: Camm/Cochran/Fry/Ohlmann/Anderson/Sweeney/Williams, Modern Business Statistics w/MS Excel 8th
Edition, 9780357929964; Chapter 3: Descriptive Statistics: Numerical Measures
Solution and Answer Guide
CAMM/COCHRAN/FRY/OHLMANN/ANDERSON/SWEENEY/WILLIAMS, MODERN BUSINESS
STATISTICS W/MS EXCEL 8TH EDITION, 9780357929964; CHAPTER 3: DESCRIPTIVE
STATISTICS: NUMERICAL MEASURES
TABLE OF CONTENTS
Practice Problems .................................................................................................................1
PRACTICE PROBLEMS
1. eICU Waiting Time: There is a severe shortage of critical care doctors and nurses to
provide intensive-care services in hospitals. To offset this shortage, many hospitals,
such as Emory Hospital in Atlanta, are using electronic intensive-care units (eICUs) to
help provide this care to patients (Emory University News Center). eICUs use electronic
monitoring tools and two-way communication through video and audio so that a
centralized staff of specially trained doctors and nurses—who can be located as far
away as Australia—can provide critical care services to patients located in remote
hospitals without fully staffed ICUs. One of the most important metrics tracked by
these eICUs is the time that a patient must wait for the first video interaction between
the patient and the eICU staff. Consider the following sample of 40 patient waiting
times until their first video interaction with the eICU staff.
a. Compute the mean waiting time for these 40 patients.
b. Compare the median waiting time.
c. Compute the mode.
d. Compute the first and third quartiles.
Solution:
a. Compute the mean waiting time for these 40 patients.
Step 1. As outlined in the Appendix: Getting Started with R and RStudio, change
the working directory to where the file eicu_r.csv is located
Step 2. To read the file and create a data frame, enter the following in the
Console pane of RStudio:
eicu_df = read.csv("eicu_r.csv")
Step 3. A summary of the descriptive statistics for the Wait Time data is created
by entering the command:
summary(eicu_df)
In this case, there is no need to create a vector for the variable Wait.Time since it
is the only variable in the data frame.
© 2025 Cengage. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible 1
website, in whole or in part.
