Chapter 1
1. The process of using sample statistics to draw conclusions about true population parameters is called
a) statistical inference.
b) the scientific method.
c) sampling.
d) descriptive statistics.
2. Those methods involving the collection, presentation, and characterization of a set of data in order to
properly describe the various features of that set of data are called
a) statistical inference.
b) the scientific method.
c) sampling.
d) descriptive statistics.
3. The universe or "totality of items or things" under consideration is called
a) a sample.
b) a population.
c) a parameter.
d) a statistic.
4. A summary measure that is computed to describe a characteristic from only a sample of the population
is called
a) a parameter.
b) a census.
c) a statistic.
d) the scientific method.
5. Which of the following is most likely a parameter as opposed to a statistic?
a) The average score of the first five students completing an assignment.
b) The proportion of females registered to vote in a county.
c) The average height of people randomly selected from a database.
d) The proportion of trucks stopped yesterday that were cited for bad brakes.
6. Most analysts focus on the cost of tuition as the way to measure the cost of a college education. But
incidentals, such as textbook costs, are rarely considered. A researcher at Drummand University wishes
to estimate the textbook costs of first-year students at Drummand. To do so, she monitored the
textbook cost of 250 first-year students and found that their average textbook cost was $300 per
semester. Identify the population of interest to the researcher.
a) All Drummand University students.
b) All college students.
c) All first-year Drummand University students.
d) The 250 students that were monitored.
7. Which of the following is a discrete quantitative variable?
a) The Dow Jones Industrial average
b) The volume of water released from a dam
c) The distance you drove yesterday.
d) The number of employees of an insurance company
8. Which of the following is a continuous quantitative variable?
a) The color of a student’s eyes
b) The number of employees of an insurance company
c) The amount of milk produced by a cow in one 24-hour period
d) The number of gallons of milk sold at the local grocery store yesterday
9. Researchers are concerned that the weight of the average American school child is increasing
implying, among other things, that children’s clothing should be manufactured and marketed in larger
sizes. If X is the weight of school children sampled in a nationwide study, then X is an example of
a) a categorical random variable.
b) a discrete random variable.
c) a continuous random variable.
d) a parameter.
10. The chancellor of a major university was concerned about alcohol abuse on her campus and wanted to
find out the proportion of students at her university who visited campus bars on the weekend before the
final exam week. Her assistant took a random sample of 250 students. The portion of students in the
sample who visited campus bars on the weekend before the final exam week is an example of
__________.
a) a categorical random variable.
b) a discrete random variable.
c) a parameter.
d) a statistic
11. True or False: A statistic is usually unobservable while a parameter is usually observable.
12. True or False: The answer to the question “How do you rate the quality of your business statistics
course” is an example of an ordinal scaled variable.
13. True or False: A professor computed the sample average exam score of 20 students and used it to
estimate the average exam score of the 1,500 students taking the exam was an example of inferential
statistics.
14. The Commissioner of Health in New York State wanted to study malpractice litigation in New York.
A sample of 31 thousand medical records was drawn from a population of 2.7 million patients who
were discharged during the year 1997. The collection, presentation, and characterization of the data
from patient medical records are examples of inferential statistics __.
15. In purchasing an automobile, there are a number of variables to consider. The color of the car is an
example of a ___ categorical ____ variable.
Chapter 2
Chapter 3
An insurance company evaluates many numerical variables about a person before deciding on an
appropriate rate for automobile insurance. A representative from a local insurance agency selected a
random sample of insured drivers and recorded, X, the number of claims each made in the last 3 years, with
the following results.
X
f
1
14
2
18
3
12
4
5
5
1
1. Referring to Table 2-1, how many drivers are represented in the sample?
a) 5
b) 15
c) 18
d) 50
2. The width of each bar in a histogram corresponds to the
a) differences between the boundaries of the class.
b) number of observations in each class.
c) midpoint of each class.
d) percentage of observations in each class.
TABLE 2-3
Every spring semester, the School of Business coordinates with local business leaders a luncheon for
graduating seniors, their families, and friends. Corporate sponsorship pays for the lunches of each of the
seniors, but students have to purchase tickets to cover the cost of lunches served to guests they bring with
them. The following histogram represents the attendance at the senior luncheon, where X is the number of
guests each graduating senior invited to the luncheon and f is the number of graduating seniors in each
category.
160
152
140
120
100
Frequency
85
80
60
40
20
18
17
3
0
4
5
0
0
1
2
Guests per Student
3
3. Referring to the histogram from Table 2-3, how many graduating seniors attended the luncheon?
a) 4
b) 152
c) 275
d) 388
A survey was conducted to determine how people rated the quality of programming available on television.
Respondents were asked to rate the overall quality from 0 (no quality at all) to 100 (extremely good
quality). The stem-and-leaf display of the data is shown below.
Stem Leaves
3
24
4
03478999
5
0112345
6
12566
7
01
8
9
2
4. Referring to Table 2-4, what percentage of the respondents rated overall television quality with a rating
of 80 or above?
a) 0
b) 4
c) 96
d) 100
TABLE 2-5
The following are the durations in minutes of a sample of long-distance phone calls made within the
continental United States reported by one long-distance carrier.
Time (in Minutes)
0 but less than 5
5 but less than 10
10 but less than 15
15 but less than 20
20 but less than 25
25 but less than 30
30 or more
Relative
Frequency
0.37
0.22
0.15
0.10
0.07
0.07
0.02
5. Referring to Table 2-5, what is the width of each class?
a) 1 minute
b) 5 minutes
c) 2%
d) 100%
6. Referring to Table 2-5, if 10 calls lasted 30 minutes or more, how many calls lasted less than 5
minutes?
a) 10
b) 185
c) 295
d) 500
7. Referring to Table 2-5, if 100 calls were sampled, _______ of them would have lasted less than 5
minutes or at least 30 minutes or more.
a) 35
b) 37
c) 39
d) None of the above.
8. When studying the simultaneous responses to two categorical questions, we should set up a
a) contingency table.
b) frequency distribution table.
c) cumulative percentage distribution table.
d) histogram.
9. You have collected information on the consumption by the 15 largest coffee-consuming nations.
Which of the following is the best for presenting the share of the consumption?
a) A pie chart.
b) A Pareto diagram
c) A side-by-side bar chart.
d) A contingency table.
10. You have collected data on the annual average amount of cash rebate offered by 6 different brands of
automobiles sold in the US in 2006 and 2007. Which of the following is the best for presenting the
data?
a) A contingency table.
b) A stem-and-leaf display
c) A time-series plot.
d) A side-by-side bar chart.
11. Referring to Table 2-12, of those for the plan in the sample, ________ percent were females.
12. Referring to Table 2-12, of the females in the sample, ________ percent were against the plan.
13. Referring to Table 2-12, ________ percent of the 200 were females who were against the plan.
The table 2-14 below contains the number of people who own a portable DVD player in a sample of 600
broken down by gender.
Own a Portable
DVD Player
Male
Female
Yes
96
40
No
224
240
14. Referring to Table 2-14, of those who owned a portable DVD in the sample, ___29.41%_____
percent were females.
15. Referring to Table 2-14, of those who did not own a portable DVD in the sample, ___51.72%_____
percent were males.
Chapter 4
1. Which of the following statistics is not a measure of central tendency?
a) Arithmetic mean.
b) Median.
c) Mode.
d) Q3.
2. Which of the arithmetic mean, median, mode, and geometric mean are resistant measures of central
tendency?
a) The arithmetic mean and median only.
b) The median and mode only.
c) The mode and geometric mean only.
d) The arithmetic mean and mode only.
3. In a perfectly symmetrical bell-shaped "normal" distribution
a) the arithmetic mean equals the median.
b) the median equals the mode.
c) the arithmetic mean equals the mode.
d) All the above.
4. In general, which of the following descriptive summary measures cannot be easily approximated from
a boxplot?
a) The variance.
b) The range.
c) The interquartile range.
d) The median.
5. In right-skewed distributions, which of the following is the correct statement?
a) The distance from Q1 to Q2 is larger than the distance from Q2 to Q3.
b) The distance from Q1 to Q2 is smaller than the distance from Q2 to Q3.
c) The arithmetic mean is smaller than the median.
d) The mode is larger than the arithmetic mean.
6. According to the empirical rule, if the data form a "bell-shaped" normal distribution, _______ percent
of the observations will be contained within 1 standard deviation around the arithmetic mean.
a) 68.26
b) 75.00
c) 88.89
d) 93.75
7. Which of the following is NOT sensitive to extreme values?
a) The range.
b) The standard deviation.
c) The interquartile range.
d) The coefficient of variation.
8. According to the Chebyshev rule, at least 93.75% of all observations in any data set are contained
within a distance of how many standard deviations around the mean?
a) 1
b) 2
c) 3
d) 4
TABLE 3-1
Health care issues are receiving much attention in both academic and political arenas. A sociologist
recently conducted a survey of citizens over 60 years of age whose net worth is too high to qualify for
Medicaid and have no private health insurance. The ages of 25 uninsured senior citizens were as follows:
60 61 62 63 64 65 66 68 68 69 70 73 73
74 75 76 76 81 81 82 86 87 89 90 92
9. Referring to Table 3-1, identify the first quartile of the ages of the uninsured senior citizens.
10. Referring to Table 3-1, identify which of the following is the correct statement.
a) One fourth of the senior citizens sampled are below 64 years of age.
b) The middle 50% of the senior citizens sampled are between 65.5 and 73.0 years of age.
c) 25% of the senior citizens sampled are older than 81.5 years of age.
d) All of the above are correct.
11. Referring to Table 3-1, calculate the coefficient of variation of the ages of the uninsured senior
citizens.
12. True or False: If the distribution of a data set were perfectly symmetrical, the distance from Q1 to the
median would always equal the distance from Q3 to the median in a boxplot.
13. True or False: The 5-number summary consists of the smallest observation, the first quartile, the
median, the third quartile, and the largest observation.
14. True or False: In a boxplot, the box portion represents the data between the first and third quartile
values.
15. True or False: The geometric mean is a measure of variation or dispersion in a set of data.
Chapter 6
1. Which of the following about the binomial distribution is not a true statement?
a) The probability of event of interest must be constant from trial to trial.
b) Each outcome is independent of the other.
c) Each outcome may be classified as either "event of interest" or "not event of interest."
d) The random variable of interest is continuous.
2. If n = 10 and p = 0.70, then the mean of the binomial distribution is
a) 0.07
b) 1.45.
c) 7.00
d) 14.29
3. If n = 10 and p = 0.70, then the standard deviation of the binomial distribution is
a) 0.07
b) 1.45
c) 7.00
d) 14.29
4. The portfolio expected return of two investments
a) will be higher when the covariance is zero.
b) will be higher when the covariance is negative.
c) will be higher when the covariance is positive.
d) does not depend on the covariance.
5. A lab orders 100 rats a week for each of the 52 weeks in the year for experiments that the lab conducts.
Prices for 100 rats follow the following distribution:
Price:
$10.00
$12.50
$15.00
Probability:
0.35
0.40
0.25
How much should the lab budget for next year’s rat orders be, assuming this distribution does not
change?
a) $520
b) $637
c) $650
d) $780
6. True or False: The number of males selected in a sample of 5 students taken without replacement from
a class of 9 females and 18 males has a binomial distribution.
7. True or False: If p remains constant in a binomial distribution, an increase in n will increase the
variance.
The probability that a particular type of smoke alarm will function properly and sound an alarm in the
presence of smoke is 0.8. You have 2 such alarms in your home and they operate independently.
8. Referring to Table 5-1, the probability that both sound an alarm in the presence of smoke is ________.
9. Referring to Table 5-1, the probability that at least one sounds an alarm in the presence of smoke is
________.
10. Referring to Table 5-1, the probability that at least one sounds an alarm in the presence of smoke is
________.
Chapter 7
1. In its standardized form, the normal distribution
a) has a mean of 0 and a standard deviation of 1.
b) has a mean of 1 and a variance of 0.
c) has an area equal to 0.5.
d) cannot be used to approximate discrete probability distributions.
2. If a particular batch of data is approximately normally distributed, we would find that approximately
a) 2 of every 3 observations would fall between  1 standard deviation around the mean.
b) 4 of every 5 observations would fall between  1.28 standard deviations around the mean.
c) 19 of every 20 observations would fall between  2 standard deviations around the mean.
d) All the above.
3. For some value of Z, the probability that a standard normal variable is below Z is 0.2090. The value of
Z is
a) – 0.81
b) – 0.31
c) 0.31
d) 1.96
4. For some positive value of X, the probability that a standard normal variable is between 0 and +1.5X is
0.4332. The value of X is
a) 0.10
b) 0.50
5.
6.
7.
8.
9.
10.
c) 1.00
d) 1.50
A company that sells annuities must base the annual payout on the probability distribution of the length
of life of the participants in the plan. Suppose the probability distribution of the lifetimes of the
participants is approximately a normal distribution with a mean of 68 years and a standard deviation of
3.5 years. What proportion of the plan recipients would receive payments beyond age 75?
If we know that the length of time it takes a college student to find a parking spot in the library parking
lot follows a normal distribution with a mean of 3.5 minutes and a standard deviation of 1 minute, find
the probability that a randomly selected college student will find a parking spot in the library parking
lot in less than 3 minutes.
a) 0.3551
b) 0.3085
c) 0.2674
d) 0.1915
True or False: The probability that a standard normal random variable, Z, is between 1.50 and 2.10 is
the same as the probability Z is between – 2.10 and – 1.50.
True or False: Theoretically, the mean, median, and the mode are all equal for a normal distribution.
The amount of pyridoxine (in grams) in a multiple vitamin is normally distributed with  = 110 grams
and  = 25 grams. What is the probability that a randomly selected vitamin will contain between 82
and 100 grams of pyridoxine?
You were told that the mean score on a statistics exam is 75 with the scores normally distributed. In
addition, you know the probability of a score between 55 and 60 is 4.41% and that the probability of a
score greater than 90 is 6.68%. The middle 95.46% of the students will score between which two
scores?
Chapter 8a
Chapter 8b
1. The width of a confidence interval estimate for a proportion will be
a) narrower for 99% confidence than for 95% confidence.
b) wider for a sample size of 100 than for a sample size of 50.
c) narrower for 90% confidence than for 95% confidence.
d) narrower when the sample proportion is 0.50 than when the sample proportion is 0.20.
2. A 99% confidence interval estimate can be interpreted to mean that
a) if all possible samples are taken and confidence interval estimates are developed, 99% of them
would include the true population mean somewhere within their interval.
b) we have 99% confidence that we have selected a sample whose interval does include the
population mean.
c) Both of the above.
d) None of the above.
3. If you were constructing a 99% confidence interval of the population mean based on a sample of n=25
where the standard deviation of the sample s = 0.05, the critical value of t will be
a) 2.7969
b) 2.7874
c) 2.4922
d) 2.4851
4. The t distribution
a) assumes the population is normally distributed.
b) approaches the normal distribution as the sample size increases.
c) has more area in the tails than does the normal distribution.
d) All of the above.
5. It is desired to estimate the average total compensation of CEOs in the Service industry. Data were
randomly collected from 18 CEOs and the 97% confidence interval was calculated to be ($2,181,260,
$5,836,180). Which of the following interpretations is correct?
a) 97% of the sampled total compensation values fell between $2,181,260 and $5,836,180.
b) We are 97% confident that the mean of the sampled CEOs falls in the interval $2,181,260 to
$5,836,180.
c) In the population of Service industry CEOs, 97% of them will have total compensations that
fall in the interval $2,181,260 to $5,836,180.
d) We are 97% confident that the average total compensation of all CEOs in the Service industry
falls in the interval $2,181,260 to $5,836,180.
6. A confidence interval was used to estimate the proportion of statistics students that are females. A
random sample of 72 statistics students generated the following 90% confidence interval: (0.438,
0.642). Based on the interval above, is the population proportion of females equal to 0.60?
a) No, and we are 90% sure of it.
b) No. The proportion is 54.17%.
c) Maybe. 0.60 is a believable value of the population proportion based on the information above.
d) Yes, and we are 90% sure of it.
7. Suppose a 95% confidence interval for  turns out to be (1,000, 2,100). To make more useful
inferences from the data, it is desired to reduce the width of the confidence interval. Which of the
following will result in a reduced interval width?
a) Increase the sample size.
b) Increase the confidence level.
c) Increase the population mean.
d) Increase the sample mean.
8. A major department store chain is interested in estimating the average amount its credit card customers
spent on their first visit to the chain’s new store in the mall. Fifteen credit card accounts were randomly
sampled and analyzed with the following results: X  $50.50 and s  400 . Construct a 95%
confidence interval for the average amount its credit card customers spent on their first visit to the
chain’s new store in the mall assuming that the amount spent follows a normal distribution.
a) $50.50  $9.09
b) $50.50  $10.12
c) $50.50  $11.00
d) $50.50  $11.08
9. A university dean is interested in determining the proportion of students who receive some sort of
financial aid. Rather than examine the records for all students, the dean randomly selects 200 students
and finds that 118 of them are receiving financial aid. If the dean wanted to estimate the proportion of
all students receiving financial aid to within 3% with 99% reliability, how many students would need
to be sampled?
a) n = 1,844
b) n = 1,784
c) n = 1,503
d) n = 1,435
10. The head librarian at the Library of Congress has asked her assistant for an interval estimate of the
mean number of books checked out each day. The assistant provides the following interval estimate:
from 740 to 920 books per day. If the head librarian knows that the population standard deviation is
150 books checked out per day, approximately how large a sample did her assistant use to determine
the interval estimate?
2
Chapter 9
1. Which of the following would be an appropriate null hypothesis?
a) The mean of a population is equal to 55.
b) The mean of a sample is equal to 55.
c) The mean of a population is greater than 55.
d) Only (a) and (c) are true.
2. Which of the following would be an appropriate alternative hypothesis?
a) The mean of a population is equal to 55.
b) The mean of a sample is equal to 55.
c) The mean of a population is greater than 55.
d) The mean of a sample is greater than 55.
3. A Type II error is committed when
a) we reject a null hypothesis that is true.
b) we don't reject a null hypothesis that is true.
c) we reject a null hypothesis that is false.
d) we don't reject a null hypothesis that is false.
4. A Type I error is committed when
5.
6.
7.
8.
a) we reject a null hypothesis that is true.
b) we don't reject a null hypothesis that is true.
c) we reject a null hypothesis that is false.
d) we don't reject a null hypothesis that is false.
The power of a test is measured by its capability of
a) rejecting a null hypothesis that is true.
b) not rejecting a null hypothesis that is true.
c) rejecting a null hypothesis that is false.
d) not rejecting a null hypothesis that is false.
If an economist wishes to determine whether there is evidence that average family income in a
community exceeds $25,000
a) either a one-tailed or two-tailed test could be used with equivalent results.
b) a one-tailed test should be utilized.
c) a two-tailed test should be utilized.
d) None of the above.
If the p-value is less than  in a two-tailed test,
a) the null hypothesis should not be rejected.
b) the null hypothesis should be rejected.
c) a one-tailed test should be used.
d) no conclusion should be reached.
How many Kleenex should the Kimberly Clark Corporation package of tissues contain? Researchers
determined that 60 tissues is the average number of tissues used during a cold. Suppose a random
sample of 100 Kleenex users yielded the following data on the number of tissues used during a cold:
X = 52, s = 22. Give the null and alternative hypotheses to determine if the number of tissues used
during a cold is less than 60.
a) H0 :   60 and H1 :   60.
b) H0 :   60 and H1 :   60.
H0 : X  60 and H1 : X  60.
d) H0 : X  52 and H1 : X  52.
c)
9. We have created a 95% confidence interval for  with the result (10, 15). What decision will we make
if we test H0 :  16 versus H1 :   16 at  = 0.10?
a) Reject H0 in favor of H1.
b) Accept H0 in favor of H1.
c) Fail to reject H0 in favor of H1.
d) We cannot tell what our decision will be from the information given.
10. The owner of a local nightclub has recently surveyed a random sample of n = 250 customers of the
club. She would now like to determine whether or not the mean age of her customers is over 30. If so,
she plans to alter the entertainment to appeal to an older crowd. If not, no entertainment changes will
be made. Suppose she found that the sample mean was 30.45 years and the sample standard deviation
was 5 years. If she wants to be 99% confident in her decision, what decision should she make?
a) Reject H0.
b) Accept H0.
c) Fail to reject H0.
d) We cannot tell what her decision should be from the information given.
11. A major videocassette rental chain is considering opening a new store in an area that currently does not
have any such stores. The chain will open if there is evidence that more than 5,000 of the 20,000
households in the area are equipped with videocassette recorders (VCRs). It conducts a telephone poll
of 300 randomly selected households in the area and finds that 96 have VCRs. The rental chain's
conclusion from the hypothesis test using a 3% level of significance is:
a) to open a new store.
b) not to open a new store.
c) to delay opening a new store until additional evidence is collected.
d) we cannot tell what the decision should be from the information given
Chapter 10
1. The t test for the difference between the means of 2 independent populations assumes that the
respective
a) sample sizes are equal.
b) sample variances are equal.
c) populations are approximately normal.
d) All of the above.
2. The t test for the mean difference between 2 related populations assumes that the
a) population sizes are equal.
b) sample variances are equal.
c) population of differences is approximately normal or sample sizes are large enough.
d) All of the above.
3. If we are testing for the difference between the means of 2 related populations with samples of n1 = 20
and n2 = 20, the number of degrees of freedom is equal to
a) 39.
b) 38.
c) 19.
d) 18.
4. In testing for differences between the means of two related populations, the null hypothesis is
a) H 0 :  D  2 .
H0 : D  0 .
c) H 0 :  D  0 .
d) H 0 :  D  0 .
b)
TABLE 10-1
Are Japanese managers more motivated than American managers? A randomly selected group of each
were administered the Sarnoff Survey of Attitudes Toward Life (SSATL), which measures motivation for
upward mobility. The SSATL scores are summarized below.
Sample Size
Mean SSATL Score
Population Std. Dev.
American
211
65.75
11.07
Japanese
100
79.83
6.41
5. Referring to Table 10-1, judging from the way the data were collected, which test would likely be most
appropriate to employ?
a) Paired t test
b) Pooled-variance t test for the difference between two means
c) Independent samples Z test for the difference between two means
d) Related samples Z test for the mean difference
6. Referring to Table 10-1, give the null and alternative hypotheses to determine if the average SSATL
score of Japanese managers differs from the average SSATL score of American managers.
a) H0 :  A –  J  0 versus H1 :  A –  J  0
b) H0 :  A –  J  0 versus H1 :  A –  J  0
c) H0 :  A –  J  0 versus H1 :  A –  J  0
d) H0 : XA – XJ  0 versus H1 : X A – XJ  0
TABLE 10-4
A real estate company is interested in testing whether, on average, families in Gotham have been living in
their current homes for less time than families in Metropolis have. Assume that the two population
variances are equal. A random sample of 100 families from Gotham and a random sample of 150 families
in Metropolis yield the following data on length of residence in current homes.
Gotham: X G = 35 months, sG2 = 900
Metropolis: X M = 50 months, sM2 = 1050
7. Referring to Table 10-4, which of the following represents the relevant hypotheses tested by the real
estate company?
a) H0 :  G – M  0 versus H1 :  G –  M  0
b) H0 : G –  M  0 versus H1 :  G –  M  0
H0 :  G – M  0 versus H1 :  G –  M  0
d) H0 : XG – XM  0 versus H1 : XG – XM  0
c)
8. Referring to Table 10-4, suppose  = 0.1. Which of the following represents the correct conclusion?
a) There is not enough evidence that, on average, families in Gotham have been living in their
current homes for less time than families in Metropolis have.
b) There is enough evidence that, on average, families in Gotham have been living in their current
homes for less time than families in Metropolis have.
c) There is not enough evidence that, on average, families in Gotham have been living in their
current homes for no less time than families in Metropolis have.
d) There is enough evidence that, on average, families in Gotham have been living in their current
homes for no less time than families in Metropolis have.
TABLE 10-5
To test the effectiveness of a business school preparation course, 8 students took a general business test
before and after the course. The results are given below.
Exam Score
Exam Score
Student Before Course (1)
After Course (2)
1
530
670
2
690
770
3
910
1,000
4
700
710
5
450
550
6
820
870
7
820
770
8
630
610
9. Referring to Table 10-5, the number of degrees of freedom is
a) 14.
b) 13.
c) 8.
d) 7.
10. Referring to Table 10-5, at the 0.05 level of significance, the conclusion for this hypothesis test would
be:
a) the business school preparation course does improve exam score.
b) the business school preparation course does not improve exam score.
c) the business school preparation course has no impact on exam score.
d) It cannot be drawn from the information given.
Chapter 12
1. The Y-intercept (b0) represents the
a) predicted value of Y when X = 0.
b) change in estimated average Y per unit change in X.
c) predicted value of Y.
d) variation around the sample regression line.
2. The slope (b1) represents
a) predicted value of Y when X = 0.
b) the estimated average change in Y per unit change in X.
c) the predicted value of Y.
d) variation around the line of regression.
TABLE 13-1
A large national bank charges local companies for using their services. A bank official reported the results
of a regression analysis designed to predict the bank’s charges (Y) -- measured in dollars per month -- for
services rendered to local companies. One independent variable used to predict service charge to a
company is the company’s sales revenue (X) -- measured in millions of dollars. Data for 21 companies who
use the bank’s services were used to fit the model:
E(Y)  0  1X
The results of the simple linear regression are provided below.
Y  2,700  20 X , SYX  65, two-tailed p value  0.034 (for testing  )
3. Referring to Table 13-1, interpret the estimate of  0 , the Y-intercept of the line.
a) All companies will be charged at least $2,700 by the bank.
b) There is no practical interpretation since a sales revenue of $0 is a nonsensical value.
c) About 95% of the observed service charges fall within $2,700 of the least squares line.
d) For every $1 million increase in sales revenue, we expect a service charge to decrease $2,700.
4. Referring to Table 13-1, a 95% confidence interval for  1 is (15, 30). Interpret the interval.
a) We are 95% confident that the mean service charge will fall between $15 and $30 per month.
b) We are 95% confident that the sales revenue (X) will increase between $15 and $30 million for
every $1 increase in service charge (Y).
c) We are 95% confident that average service charge (Y) will increase between $15 and $30 for
every $1 million increase in sales revenue (X).
d) At the  = 0.05 level, there is no evidence of a linear relationship between service charge (Y)
and sales revenue (X).
TABLE 13-2
A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their
product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different
prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear
regression on the data below:
City
Price ($) Sales
River Falls
1.30
100
Hudson
1.60
90
Ellsworth
1.80
90
Prescott
2.00
40
Rock Elm
2.40
38
Stillwater
2.90
32
5. Referring to Table 13-2, what is the estimated slope parameter for the candy bar price and sales data?
a) 161.386
b) 0.784
c) – 3.810
d) – 48.193
6. Referring to Table 13-2, what is the estimated average change in the sales of the candy bar if price goes
up by $1.00?
a) 161.386
b) 0.784
c) – 3.810
d) – 48.193
7. Referring to Table 13-2, what is the percentage of the total variation in candy bar sales explained by
the regression model?
a) 100%
b) 88.54%
c) 78.39%
d) 48.19%
8. Referring to Table 13-2, to test that the regression coefficient,  1 , is not equal to 0, what would be the
critical values? Use  = 0.05.
a)  2.5706
b)  2.7764
c)  3.1634
d)  3.4954
9. Referring to Table 13-2, if the price of the candy bar is set at $2, the estimated average sales will be
a) 30
b) 65
c) 90
d) 100
10. True of False: The Chancellor of a university has commissioned a team to collect data on students’
GPAs and the amount of time they spend bar hopping every week (measured in minutes). He wants to
know if imposing much tougher regulations on all campus bars to make it more difficult for students to
spend time in any campus bar will have a significant impact on general students' GPAs. His team
should use a t test on the slope of the population regression.
TABLE 13-4
The managers of a brokerage firm are interested in finding out if the number of new clients a broker brings
into the firm affects the sales generated by the broker. They sample 12 brokers and determine the number
of new clients they have enrolled in the last year and their sales amounts in thousands of dollars. These
data are presented in the table that follows.
Broker
Clients
Sales
1
27
52
2
11
37
3
42
64
4
33
55
5
15
29
6
15
34
7
25
58
8
36
59
9
28
44
10
30
48
11
17
31
12
22
38
11. Referring to Table 13-4, the least squares estimate of the slope is __________.
12. Referring to Table 13-4, the least squares estimate of the Y-intercept is __________.
13. Referring to Table 13-4, the prediction for the amount of sales (in $1,000s) for a person who brings 25
new clients into the firm is ________.
14. Referring to Table 13-4, ______% of the total variation in sales generated can be explained by the
number of new clients brought in.
Chapter 13
1. In a multiple regression problem involving two independent variables, if b1 is computed to be +2.0, it
means that
a) the relationship between X1 and Y is significant.
b) the estimated average of Y increases by 2 units for each increase of 1 unit of X1, holding X2
constant.
c) the estimated average of Y increases by 2 units for each increase of 1 unit of X1, without regard
to X2.
d) the estimated average of Y is 2 when X1 equals zero.
2. In a multiple regression model, the value of the coefficient of multiple determination
a) has to fall between -1 and +1.
b) has to fall between 0 and +1.
c) has to fall between -1 and 0.
d) can fall between any pair of real numbers.
A manager of a product sales group believes the number of sales made by an employee (Y) depends on how
many years that employee has been with the company (X1) and how he/she scored on a business aptitude
test (X2). A random sample of 8 employees provides the following:
Employee Y
X1
X2
1
100
10
7
2
90
3
10
3
80
8
9
4
70
5
4
5
60
5
8
6
50
7
5
7
40
1
4
8
30
1
1
3. Referring to Table 14-1, for these data, what is the value for the regression constant, b0?
a) 0.998
b) 3.103
c) 4.698
d) 21.293
4. Referring to Table 14-1, for these data, what is the estimated coefficient for the variable representing
years an employee has been with the company, b1?
a) 0.998
b) 3.103
c) 4.698
d) 21.293
5. Referring to Table 14-1, for these data, what is the estimated coefficient for the variable representing
scores on the aptitude test, b2?
a) 0.998
b) 3.103
c) 4.698
d) 21.293
6. Referring to Table 14-1, if an employee who had been with the company 5 years scored a 9 on the
aptitude test, what would his estimated expected sales be?
a) 79.09
b) 60.88
c) 55.62
d) 17.98
7. The variation attributable to factors other than the relationship between the independent variables and
the explained variable in a regression analysis is represented by
a) regression sum of squares.
b) error sum of squares.
c) total sum of squares.
d) regression mean squares.
TABLE 14-3
An economist is interested to see how consumption for an economy (in $ billions) is influenced by gross
domestic product ($ billions) and aggregate price (consumer price index). The Microsoft Excel output of
this regression is partially reproduced below.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.991
R Square
0.982
Adjusted R Square
0.976
Standard Error
0.299
Observations
10
ANOVA
Regression
Residual
Total
Intercept
GDP
Price
df
2
7
9
Coeff
– 0.0861
0.7654
– 0.0006
SS
33.4163
0.6277
34.0440
StdError
0.5674
0.0574
0.0028
MS
16.7082
0.0897
t Stat
– 0.152
13.340
– 0.219
F
186.325
P-value
0.8837
0.0001
0.8330
Signif F
0.0001
8. Referring to Table 14-3, when the economist used a simple linear regression model with consumption
as the dependent variable and GDP as the independent variable, he obtained an r2 value of 0.971. What
additional percentage of the total variation of consumption has been explained by including aggregate
prices in the multiple regression?
a) 98.2
b) 11.1
c) 2.8
d) 1.1
9. Referring to Table 14-3, the p-value for GDP is
a) 0.05
b) 0.01
c) 0.001
d) None of the above.
10. Referring to Table 14-3, the p-value for the regression model as a whole is
a) 0.05
b) 0.01
c) 0.001
d) None of the above.
11. Referring to Table 14-3, what is the predicted consumption level for an economy with GDP equal to $4
billion and an aggregate price index of 150?
a) $1.39 billion
b) $2.89 billion
c) $4.75 billion
d) $9.45 billion