Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
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 work
stations, 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:
, Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
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.
, Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
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 in the population 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
coming year and compare to costs to determine profitability.
3) total amount of sulfuric acid purchased per month for use in
battery production. - can be used by management to study wasted
inventory, scrap, etc.
, Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
4) total amount of defective and/or rejected units produced per
day/week/month. - can be used by management to study wasted
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 consumers 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 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 percent 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.
Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
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 work
stations, 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:
, Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
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.
, Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
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 in the population 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
coming year and compare to costs to determine profitability.
3) total amount of sulfuric acid purchased per month for use in
battery production. - can be used by management to study wasted
inventory, scrap, etc.
, Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
Black, Bayley, Castillo: Business Statistics, Third Canadian Edition solutions manual
4) total amount of defective and/or rejected units produced per
day/week/month. - can be used by management to study wasted
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 consumers 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 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 percent 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.
