,SOLUTION MANUAL FOR Business Statistics, 11e
Black
Notes
1- The file is chapter after chapter.
2- We have shown you few pages sample.
3- The file contains all Appendix and Excel sheet
if it exists.
4- We have all what you need, we make update
at every time. There are many new editions
waiting you.
5- If you think you purchased the wrong file You
can contact us at every time, we can replace it
with true one.
Our email:
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
SOLUTIONS TO PROBLEMS IN
CHAPTER 1: INTRODUCTION TO STATISTICS
1.1 Examples of data in business disciplines:
accounting – revenue/sales, cost of goods, salary expense, depreciation,
utility costs, taxes, equipment inventory, etc.
finance - World bank bond rates, number of failed savings and loans
companies, measured risk of common stocks, stock dividends, foreign
exchange rate, liquidity rates for a single-family, etc.
human resources - salaries, size of engineering staff, years’ experience,
age of employees, years of education, etc.
marketing - number of units sold, dollar sales volume, forecast sales, size
of sales force, market share, measurement of consumer motivation,
measurement of consumer frustration, measurement of brand preference,
attitude measurement, measurement of consumer risk, etc.
operations and supply chain management - the number, location, and
network missions of suppliers, production facilities, distribution centers,
warehouses, cross-docks, and customers; the quantity and location of
inventory, including raw materials, work in process (WIP), and finished
goods, etc.
information systems - CPU time, size of memory, number of workstations,
storage capacity, percent of professionals who are connected to a
computer network, dollar assets of company computing, number of “hits”
on the Internet, time spent on the Internet per day, percentage of people
who use the Internet, retail dollars spent in e-commerce, etc.
production - number of production runs per day, weight of a product;
assembly time, number of defects per run, temperature in the plant,
amount of inventory, turnaround time, etc.
management - measurement of union participation, measurement of
employer support, measurement of tendency to control, number of
subordinates reporting to a manager, measurement of leadership style, etc.
1.2 Examples of data that can be gathered for decision-making purposes in
business industries:
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strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
manufacturing - size of punched hole, number of rejects, amount of
inventory, amount of production, number of production workers, etc.
insurance - number of claims per month, average amount of life insurance
per family head, life expectancy, cost of repairs for major auto collision,
average medical costs incurred for a single female over 45 years of age,
etc.
travel - cost of airfare, number of miles traveled for ground transported
vacations, number of nights away from home, size of traveling party,
amount spent per day on vacation besides lodging, etc.
retailing - inventory turnover ratio, sales volume, size of sales force,
number of competitors within 2 miles of retail outlet, area of store, number
of sales people, etc.
communications - cost per minute, number of phones per office, miles of
cable per customer headquarters, minutes per day of long distance usage,
number of operators, time between calls, etc.
computing - age of company hardware, cost of software, number of
CAD/CAM stations, age of computer operators, measure to evaluate
competing software packages, size of data base, etc.
agriculture - number of farms per county, farm income, number of acres of
corn per farm, wholesale price of a gallon of milk, number of livestock,
grain storage capacity, etc.
banking - size of deposit, number of failed banks, amount loaned to
foreign banks, number of tellers per drive-in facility, average amount of
withdrawal from automatic teller machine, federal reserve discount rate,
etc.
healthcare - number of patients per physician per day, average cost of
hospital stay, average daily census of hospital, time spent waiting to see a
physician, patient satisfaction, number of blood tests done per week.
1.3 Descriptive statistics in recorded music industry :
1) RCA total sales of compact discs this week, number of artists
under contract to a company at a given time.
2) total dollars spent on advertising last month to promote an album.
3) number of units produced in a day.
Solutions Manual 1-2 Chapter 1
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strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
4) number of retail outlets selling the company's products.
Inferential statistics in recorded music industry:
1) Measure the average amount spent per month on recorded music
for a few consumers, then use that figure to infer the average
amount for the population.
2) Determination of market share for rap music by using the
proportion of a randomly selected sample of 500 purchasers of
recorded music who purchased rap music.
3) Determination of top ten single records by sampling the number of
requests at a few radio stations.
4) Estimation of the average length of a single recording by using the
average length of a sample of records.
The difference between descriptive and inferential statistics lies mainly in
the usage of the data. These descriptive examples all gather data from
every item about which the description is being made. For example, RCA
measures the sales on all its compact discs for a week and reports the total.
In each of the inferential statistics examples, a sample of the population is
taken, and the population value is estimated or inferred from the sample.
For example, it may be practically impossible to determine the proportion
of buyers who prefer rap music. However, a random sample of buyers can
be contacted and interviewed for music preference. The results can be
inferred to population market share.
1.4 Descriptive statistics in manufacturing batteries to make better decisions:
1) total number of worker hours per plant per week - help
management understand labor costs, work allocation, productivity,
etc.
2) company sales volume of batteries in a year - help management
decide if the product is profitable, how much to advertise in the
coming year and compare to costs to determine profitability.
3) total amount of lithium purchased per month for use in battery
production. - can be used by management to study wasted
inventory, scrap, etc.
4) total amount of defective and/or rejected units produced per
day/week/month. - can be used by management to study wasted
Solutions Manual 1-3 Chapter 1
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strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
resources, need for labor training, redesign of assembly process,
etc.
Inferential Statistics in manufacturing batteries to make decisions:
1) Take a sample of batteries and test them to determine the average
shelf life - use the sample average to reach conclusions about all
batteries of this type. Management can then make labeling and
advertising claims. They can compare these figures to the shelf-
life of competing batteries.
2) Take a sample of battery purchasers and determine how many
batteries they purchase per year. Infer to the entire population -
management can use this information to estimate market potential
and penetration.
3) Interview a random sample of production workers to determine
attitude towards company management - management can use this
survey results to ascertain employee morale and to direct efforts
towards creating a more positive working environment which,
hopefully, results in greater productivity.
1.5 1) Size of sale ($) per customer in men’s formal wear. Either by
taking a sample or using a census, management could compute the
average sale in men’s formal wear of a weekly period and compare
the number to the same average taken a year ago or a month ago to
determine if more is being purchased per customer. Other
variables might include the number of sales per hour, number of
people entering the department per day, number of dress shirts sold
per day, etc.
2) Number of employees working per day. This variable could
indicate the day of the week (certain days have more or less sales),
sales activity (how sales are doing overall), or even health of
associates. Other variables might include the percentage of
employees absent due to illness, average number of hours worked
per week per employee, number of open positions, etc.
3) Inventory turnover rate. How fast are items in the store selling?
Other variables might include reorder rate, percent of storage space
utilized, number of stockouts per week, etc.
4) Number of customers that enter the store per hour. This figure will
vary by day, time of day, and season. Comparing figures on this
variable from period to period can give some indication of sales
Solutions Manual 1-4 Chapter 1
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strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
trends which can help drive human resource planning, etc. Other
variables might include amount of time spent per customer in the
store per visit, distance that customers travel to shop in the store,
number of referrals that customers make to other people annually,
etc.
5) Percentage of people paying with cash. Percentage of people using
credit cards. These can be used to expedite pay systems,
investigate employee theft, calculate surcharges associated with
credit cards, etc. Other variables might include average time per
checkout, average wait time in pay line, etc.
1.6 1) Size of bill or tab. This variable is the total amount in dollars spent
by a patron per visit to the restaurant. The bill or tab could be for
an individual or a group and would include both food and
beverages if they are all included in the bill. Of course, the
measurement would be in dollars. This information could be very
useful for the manager or owner to know the average size of a bill
both in projecting out total revenues over a period or as a baseline
before a marketing effort to increase sales.
2) Percentage of Capacity Filled. This variable could be measured at
various intervals, times, and days of the week. The measurement
would be calculated by taking the number of patrons in the
restaurant at any one time divided by the total number of seats in
the restaurant (capacity). From this, management could make
staffing decisions for various times and days of the week. In
addition, management could make decisions about when to
expand, how much to advertise, and/or when to run specials.
3) Length of Stay. The measurement is how many minutes people are
actually in the restaurant from the time they are assigned a table
until they are leaving. From this, management could determine
customer turnover rates which have capacity implications. That is,
how many times in a day is an average table “turned over”. If
people stay longer, do they spend more?
4) Number of Arrivals per 5-minute intervals. The measurement is
how many customers arrive at the front door to be greeted by the
hosat/maître‘d in any given five-minute period. This figure will
likely vary by day of the week, season of the year, and time of day.
Management can use this information for staffing decisions and
planning.
1.7 a) ratio
b) ratio
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, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
c) ordinal
d) nominal
e) ordinal
f) ratio
g) nominal
h) ratio
1.8 a) ordinal
b) ratio
c) nominal
d) ratio
e) ratio
f) ratio
g) nominal
h) ordinal
1.9 a) The population for this study is the 900 electric contractors who
purchased Mapletech’s wire.
b) The sample is the randomly chosen group of 35 contractors.
c) The statistic is the average satisfaction score for the sample of
thirty-five contractors.
d) The parameter is the average satisfaction score for all 900 electric
contractors in the population.
Solutions Manual 1-6 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
Legal Notice
Copyright
Copyright © 2023 by John Wiley & Sons Canada, Ltd. or related companies. All
rights reserved.
The data contained in these files are protected by copyright. This manual is
furnished under licence and may be used only in accordance with the terms of
such licence.
The material provided herein may not be downloaded, reproduced, stored in a
retrieval system, modified, made available on a network, used to create
derivative works, or transmitted in any form or by any means, electronic,
mechanical, photocopying, recording, scanning, or otherwise without the prior
written permission of John Wiley & Sons Canada, Ltd.
Solutions Manual 1-7 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
SOLUTIONS TO PROBLEMS IN CHAPTER 2
2.1
a)
Range = max-min = 29-(-12) = 41
Class width = 41/5 = 8.2 ≈ 9
The 5 class frequency distribution:
Class Interval Frequency
–15 - under –6 7
–6 - under 3 12
3 - under 12 13
12 - under 21 9
21 - under 30 9
Totals 50
b) Class width = 41/10 = 4.1 ≈ 5. 10 class frequency distribution:
Class Interval Frequency
–15 - under –10 2
–10 - under –5 5
–5 - under 0 7
0 - under 5 10
5 - under 10 7
10 - under 15 3
15 - under 20 7
20 - under 25 4
25 - under 30 5
30 - under 35 0
Totals 50
c) The frequency distribution with ten classes gives a more detailed breakdown of
temperatures. It allows locating more accurately the temperatures with the greatest frequency.
The class with the highest frequency (modal class), is 0 – under 5 class with a frequency of 10.
The five-class distribution aggregates the intervals into broader classes making it appear that
there are nearly equal frequencies in each class.
Solutions Manual 1-1 Chapter 2
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is strictly
prohibited.
Black
Notes
1- The file is chapter after chapter.
2- We have shown you few pages sample.
3- The file contains all Appendix and Excel sheet
if it exists.
4- We have all what you need, we make update
at every time. There are many new editions
waiting you.
5- If you think you purchased the wrong file You
can contact us at every time, we can replace it
with true one.
Our email:
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
SOLUTIONS TO PROBLEMS IN
CHAPTER 1: INTRODUCTION TO STATISTICS
1.1 Examples of data in business disciplines:
accounting – revenue/sales, cost of goods, salary expense, depreciation,
utility costs, taxes, equipment inventory, etc.
finance - World bank bond rates, number of failed savings and loans
companies, measured risk of common stocks, stock dividends, foreign
exchange rate, liquidity rates for a single-family, etc.
human resources - salaries, size of engineering staff, years’ experience,
age of employees, years of education, etc.
marketing - number of units sold, dollar sales volume, forecast sales, size
of sales force, market share, measurement of consumer motivation,
measurement of consumer frustration, measurement of brand preference,
attitude measurement, measurement of consumer risk, etc.
operations and supply chain management - the number, location, and
network missions of suppliers, production facilities, distribution centers,
warehouses, cross-docks, and customers; the quantity and location of
inventory, including raw materials, work in process (WIP), and finished
goods, etc.
information systems - CPU time, size of memory, number of workstations,
storage capacity, percent of professionals who are connected to a
computer network, dollar assets of company computing, number of “hits”
on the Internet, time spent on the Internet per day, percentage of people
who use the Internet, retail dollars spent in e-commerce, etc.
production - number of production runs per day, weight of a product;
assembly time, number of defects per run, temperature in the plant,
amount of inventory, turnaround time, etc.
management - measurement of union participation, measurement of
employer support, measurement of tendency to control, number of
subordinates reporting to a manager, measurement of leadership style, etc.
1.2 Examples of data that can be gathered for decision-making purposes in
business industries:
Solutions Manual 1-1 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
manufacturing - size of punched hole, number of rejects, amount of
inventory, amount of production, number of production workers, etc.
insurance - number of claims per month, average amount of life insurance
per family head, life expectancy, cost of repairs for major auto collision,
average medical costs incurred for a single female over 45 years of age,
etc.
travel - cost of airfare, number of miles traveled for ground transported
vacations, number of nights away from home, size of traveling party,
amount spent per day on vacation besides lodging, etc.
retailing - inventory turnover ratio, sales volume, size of sales force,
number of competitors within 2 miles of retail outlet, area of store, number
of sales people, etc.
communications - cost per minute, number of phones per office, miles of
cable per customer headquarters, minutes per day of long distance usage,
number of operators, time between calls, etc.
computing - age of company hardware, cost of software, number of
CAD/CAM stations, age of computer operators, measure to evaluate
competing software packages, size of data base, etc.
agriculture - number of farms per county, farm income, number of acres of
corn per farm, wholesale price of a gallon of milk, number of livestock,
grain storage capacity, etc.
banking - size of deposit, number of failed banks, amount loaned to
foreign banks, number of tellers per drive-in facility, average amount of
withdrawal from automatic teller machine, federal reserve discount rate,
etc.
healthcare - number of patients per physician per day, average cost of
hospital stay, average daily census of hospital, time spent waiting to see a
physician, patient satisfaction, number of blood tests done per week.
1.3 Descriptive statistics in recorded music industry :
1) RCA total sales of compact discs this week, number of artists
under contract to a company at a given time.
2) total dollars spent on advertising last month to promote an album.
3) number of units produced in a day.
Solutions Manual 1-2 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
4) number of retail outlets selling the company's products.
Inferential statistics in recorded music industry:
1) Measure the average amount spent per month on recorded music
for a few consumers, then use that figure to infer the average
amount for the population.
2) Determination of market share for rap music by using the
proportion of a randomly selected sample of 500 purchasers of
recorded music who purchased rap music.
3) Determination of top ten single records by sampling the number of
requests at a few radio stations.
4) Estimation of the average length of a single recording by using the
average length of a sample of records.
The difference between descriptive and inferential statistics lies mainly in
the usage of the data. These descriptive examples all gather data from
every item about which the description is being made. For example, RCA
measures the sales on all its compact discs for a week and reports the total.
In each of the inferential statistics examples, a sample of the population is
taken, and the population value is estimated or inferred from the sample.
For example, it may be practically impossible to determine the proportion
of buyers who prefer rap music. However, a random sample of buyers can
be contacted and interviewed for music preference. The results can be
inferred to population market share.
1.4 Descriptive statistics in manufacturing batteries to make better decisions:
1) total number of worker hours per plant per week - help
management understand labor costs, work allocation, productivity,
etc.
2) company sales volume of batteries in a year - help management
decide if the product is profitable, how much to advertise in the
coming year and compare to costs to determine profitability.
3) total amount of lithium purchased per month for use in battery
production. - can be used by management to study wasted
inventory, scrap, etc.
4) total amount of defective and/or rejected units produced per
day/week/month. - can be used by management to study wasted
Solutions Manual 1-3 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
resources, need for labor training, redesign of assembly process,
etc.
Inferential Statistics in manufacturing batteries to make decisions:
1) Take a sample of batteries and test them to determine the average
shelf life - use the sample average to reach conclusions about all
batteries of this type. Management can then make labeling and
advertising claims. They can compare these figures to the shelf-
life of competing batteries.
2) Take a sample of battery purchasers and determine how many
batteries they purchase per year. Infer to the entire population -
management can use this information to estimate market potential
and penetration.
3) Interview a random sample of production workers to determine
attitude towards company management - management can use this
survey results to ascertain employee morale and to direct efforts
towards creating a more positive working environment which,
hopefully, results in greater productivity.
1.5 1) Size of sale ($) per customer in men’s formal wear. Either by
taking a sample or using a census, management could compute the
average sale in men’s formal wear of a weekly period and compare
the number to the same average taken a year ago or a month ago to
determine if more is being purchased per customer. Other
variables might include the number of sales per hour, number of
people entering the department per day, number of dress shirts sold
per day, etc.
2) Number of employees working per day. This variable could
indicate the day of the week (certain days have more or less sales),
sales activity (how sales are doing overall), or even health of
associates. Other variables might include the percentage of
employees absent due to illness, average number of hours worked
per week per employee, number of open positions, etc.
3) Inventory turnover rate. How fast are items in the store selling?
Other variables might include reorder rate, percent of storage space
utilized, number of stockouts per week, etc.
4) Number of customers that enter the store per hour. This figure will
vary by day, time of day, and season. Comparing figures on this
variable from period to period can give some indication of sales
Solutions Manual 1-4 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
trends which can help drive human resource planning, etc. Other
variables might include amount of time spent per customer in the
store per visit, distance that customers travel to shop in the store,
number of referrals that customers make to other people annually,
etc.
5) Percentage of people paying with cash. Percentage of people using
credit cards. These can be used to expedite pay systems,
investigate employee theft, calculate surcharges associated with
credit cards, etc. Other variables might include average time per
checkout, average wait time in pay line, etc.
1.6 1) Size of bill or tab. This variable is the total amount in dollars spent
by a patron per visit to the restaurant. The bill or tab could be for
an individual or a group and would include both food and
beverages if they are all included in the bill. Of course, the
measurement would be in dollars. This information could be very
useful for the manager or owner to know the average size of a bill
both in projecting out total revenues over a period or as a baseline
before a marketing effort to increase sales.
2) Percentage of Capacity Filled. This variable could be measured at
various intervals, times, and days of the week. The measurement
would be calculated by taking the number of patrons in the
restaurant at any one time divided by the total number of seats in
the restaurant (capacity). From this, management could make
staffing decisions for various times and days of the week. In
addition, management could make decisions about when to
expand, how much to advertise, and/or when to run specials.
3) Length of Stay. The measurement is how many minutes people are
actually in the restaurant from the time they are assigned a table
until they are leaving. From this, management could determine
customer turnover rates which have capacity implications. That is,
how many times in a day is an average table “turned over”. If
people stay longer, do they spend more?
4) Number of Arrivals per 5-minute intervals. The measurement is
how many customers arrive at the front door to be greeted by the
hosat/maître‘d in any given five-minute period. This figure will
likely vary by day of the week, season of the year, and time of day.
Management can use this information for staffing decisions and
planning.
1.7 a) ratio
b) ratio
Solutions Manual 1-5 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
c) ordinal
d) nominal
e) ordinal
f) ratio
g) nominal
h) ratio
1.8 a) ordinal
b) ratio
c) nominal
d) ratio
e) ratio
f) ratio
g) nominal
h) ordinal
1.9 a) The population for this study is the 900 electric contractors who
purchased Mapletech’s wire.
b) The sample is the randomly chosen group of 35 contractors.
c) The statistic is the average satisfaction score for the sample of
thirty-five contractors.
d) The parameter is the average satisfaction score for all 900 electric
contractors in the population.
Solutions Manual 1-6 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
Legal Notice
Copyright
Copyright © 2023 by John Wiley & Sons Canada, Ltd. or related companies. All
rights reserved.
The data contained in these files are protected by copyright. This manual is
furnished under licence and may be used only in accordance with the terms of
such licence.
The material provided herein may not be downloaded, reproduced, stored in a
retrieval system, modified, made available on a network, used to create
derivative works, or transmitted in any form or by any means, electronic,
mechanical, photocopying, recording, scanning, or otherwise without the prior
written permission of John Wiley & Sons Canada, Ltd.
Solutions Manual 1-7 Chapter 1
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is
strictly prohibited.
, Black, Bayley, Castillo: Business Statistics, Fourth Canadian Edition
SOLUTIONS TO PROBLEMS IN CHAPTER 2
2.1
a)
Range = max-min = 29-(-12) = 41
Class width = 41/5 = 8.2 ≈ 9
The 5 class frequency distribution:
Class Interval Frequency
–15 - under –6 7
–6 - under 3 12
3 - under 12 13
12 - under 21 9
21 - under 30 9
Totals 50
b) Class width = 41/10 = 4.1 ≈ 5. 10 class frequency distribution:
Class Interval Frequency
–15 - under –10 2
–10 - under –5 5
–5 - under 0 7
0 - under 5 10
5 - under 10 7
10 - under 15 3
15 - under 20 7
20 - under 25 4
25 - under 30 5
30 - under 35 0
Totals 50
c) The frequency distribution with ten classes gives a more detailed breakdown of
temperatures. It allows locating more accurately the temperatures with the greatest frequency.
The class with the highest frequency (modal class), is 0 – under 5 class with a frequency of 10.
The five-class distribution aggregates the intervals into broader classes making it appear that
there are nearly equal frequencies in each class.
Solutions Manual 1-1 Chapter 2
Copyright © 2023 John Wiley & Sons Canada, Ltd. Unauthorized copying, distribution, or transmission of this page is strictly
prohibited.
