True or False: TABLE 17-11
A logistic regression model was estimated in order to predict the probability that a
randomly chosen university or college would be a private university using information
on mean total Scholastic Aptitude Test score (SAT) at the university or college, the
room and board expense measured in thousands of dollars (Room/Brd), and whether the
TOEFL criterion is at least 550 (Toefl550 = 1 if yes, 0 otherwise.) The dependent
variable, Y, is school type (Type = 1 if private and 0 otherwise).
Referring to Table 17-11, there is not enough evidence to conclude that Toefl500 makes
a significant contribution to the model in the presence of the other independent
variables at a 0.05 level of significance.
True or False: Some business analytics involve starting with many variables and are
then followed by filtering the data by exploring specific combinations of categorical
values or numerical range. In Excel, this approach is mimicked by using a drill-down.
True or False: TABLE 19-6
A student wanted to find out the optimal strategy to study for a Business Statistics
exam. He constructed the following payoff table based on the mean amount of time he
needed to study every week for the course and the degree of difficulty of the exam.
From the information that he gathered from students who had taken the course, he
concluded that there was a 40% probability that the exam would be easy.
Referring to Table 19-6, the optimal strategy using the expected opportunity loss
criterion is to study 8 hours per week on average for the exam.
True or False: TABLE 17-8
The superintendent of a school district wanted to predict the percentage of students
passing a sixth-grade proficiency test. She obtained the data on percentage of students
passing the proficiency test (% Passing), daily mean of the percentage of students
attending class (% Attendance), mean teacher salary in dollars (Salaries), and
instructional spending per pupil in dollars (Spending) of 47 schools in the state.
Following is the multiple regression output with Y = % Passing as the dependent
variable, X1 = % Attendance, X2 = Salaries and X3 = Spending:
Referring to Table 17-8, you can conclude that the mean teacher salary has no impact
on the mean percentage of students passing the proficiency test at a 5% level of
significance using the 95% confidence interval estimate for β2.
True or False: The changes in the price of the least consumed commodities are overly
influential in a weighted aggregate price index.
True or False: There is no significant difference between filtering performed in a
complex real-world business analytic and filtering performed using the slicers in a
PivotTable in Excel.
True or False: Repeated measurements from the same individuals is an example of data
collected from two related populations.
TABLE 8-17
A random sample of 100 stores from a large chain of 500 garden supply stores was
selected to determine the mean number of lawnmowers sold at an end-of-season
clearance sale. The sample results indicated a mean of 6 and a standard deviation of 2
lawnmowers sold. A 95% confidence interval (5.623 to 6.377) was established based on
these results.
True or False: Referring to Table 8-17, we do not know for sure whether the true
population mean is between 5.623 and 6.377 lawnmowers sold.
TABLE 8-1
The managers of a company are worried about the morale of their employees. In order
to determine if a problem in this area exists, they decide to evaluate the attitudes of their
employees with a standardized test. They select the Fortunato test of job satisfaction,
which has a known standard deviation of 24 points.
True or False: Referring to Table 8-1, this confidence interval is only valid if the scores
on the Fortunato test are normally distributed.
TABLE 11-11
A student team in a business statistics course designed an experiment to investigate
whether the brand of bubblegum used affected the size of bubbles they could blow. To
reduce the person-to-person variability, the students decided to use a randomized block
design using themselves as blocks.
Four brands of bubblegum were tested. A student chewed two pieces of a brand of gum
and then blew a bubble, attempting to make it as big as possible. Another student
measured the diameter of the bubble at its biggest point. The following table gives the
diameters of the bubbles (in inches) for the 16 observations.
True or False: Referring to Table 11-11, the decision made at a 0.05 level of
significance on the F test for the block effects implies that the blocking has been
advantageous in reducing the experiment error.
The superintendent of a school district wanted to predict the percentage of students
passing a sixth-grade proficiency test. She obtained the data on percentage of students
passing the proficiency test (% Passing), daily mean of the percentage of students
attending class (% Attendance), mean teacher salary in dollars (Salaries), and
instructional spending per pupil in dollars (Spending) of 47 schools in the state. She
believed that holding everything else constant, instructional spending per pupil had a
positive but decreasing impact on percentage. Which of the following would be the
most appropriate analysis to perform?
A) Autoregressive modeling
B) Exponential smoothing
C) Least-squares forecasting with monthly or quarterly data
D) Linear regression with log transformation
TABLE 11-1
An airline wants to select a computer software package for its reservation system. Four
software packages (1, 2, 3, and 4) are commercially available. The airline will choose
the package that bumps as few passengers as possible during a month. An experiment is
set up in which each package is used to make reservations for 5 randomly selected
weeks. (A total of 20 weeks was included in the experiment.) The number of passengers
bumped each week is obtained, which gives rise to the following Excel output:
ANOVA
Referring to Table 11-1, at a significance level of 1%,
A) there is insufficient evidence to conclude that the mean number of customers
bumped by the 4 packages are not all the same.
B) there is insufficient evidence to conclude that the mean number of customers
bumped by the 4 packages are all the same.
C) there is sufficient evidence to conclude that the mean number of customers bumped
by the 4 packages are not all the same.
D) there is sufficient evidence to conclude that the mean number of customers bumped
by the 4 packages are all the same.
TABLE 17-10
Given below are results from the regression analysis where the dependent variable is
the number of weeks a worker is unemployed due to a layoff (Unemploy) and the
independent variables are the age of the worker (Age), the number of years of education
received (Edu), the number of years at the previous job (Job Yr), a dummy variable for
marital status (Married: 1 = married, 0 = otherwise), a dummy variable for head of
household (Head: 1 = yes, 0 = no) and a dummy variable for management position
(Manager: 1 = yes, 0 = no). We shall call this Model 1. The coefficient of partial
determination ( ) of each of the 6 predictors are, respectively,
0.2807, 0.0386, 0.0317, 0.0141, 0.0958, and 0.1201.
Model 2 is the regression analysis where the dependent variable is Unemploy and the
independent variables are Age and Manager. The results of the regression analysis are
given below:
Referring to Table 17-10, Model 1, which of the following is a correct statement?
A) On average, those who are in a management position are estimated to stay jobless
shorter by approximately 1.35 weeks while holding constant the effects of all the
remaining independent variables.
B) On average, those who are in a management position are estimated to stay jobless
shorter by approximately 5.22 weeks while holding constant the effects of all the
remaining independent variables.
C) On average, those who are in a management position are estimated to stay jobless
shorter by approximately 14.30 weeks while holding constant the effects of all the
remaining independent variables.
D) On average, those who are in a management position are estimated to stay jobless
shorter by approximately 24.82 weeks while holding constant the effects of all the
remaining independent variables.
The superintendent of a school district wanted to predict the percentage of students
passing a sixth-grade proficiency test. She obtained the data on percentage of students
passing the proficiency test (% Passing), daily mean of the percentage of students
attending class (% Attendance), mean teacher salary in dollars (Salaries), and
instructional spending per pupil in dollars (Spending) of 47 schools in the state. She
believed that holding everything else constant, instructional spending per pupil had a
positive but decreasing impact on percentage. Which of the following would be the
most appropriate analysis to perform?
A) Autoregressive modeling
B) Exponential smoothing
C) Least-squares forecasting with monthly or quarterly data
D) Linear regression with log transformation
The following is the list of MAD statistics for each of the models you have estimated
from time-series data:
Based on the MAD criterion, the most appropriate model is
A) linear trend.
B) quadratic trend.
C) exponential trend.
D) second-order autoregressive.
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 $600 per semester. Identify the variable of
interest to the researcher.
A) The textbook cost of first-year Drummand University students
B) The year in school of Drummand University students
C) The age of Drummand University students
D) The cost of incidental expenses of Drummand University students
At a computer manufacturing company, the actual size of computer chips is normally
distributed with a mean of 1 centimeter and a standard deviation of 0.1 centimeter. A
random sample of 12 computer chips is taken. What is the standard error for the sample
mean?
A) 0.029
B) 0.050
C) 0.091
D) 0.120
TABLE 1-2
A Wall Street Journal poll asked 2,150 adults in the United States a series of questions
to find out their view on the U.S. economy.
Referring to Table 1-2, the 2,150 adults make up
A) the population.
B) the sample.
C) the primary data source.
D) the secondary data source.
A few years ago, Pepsi invited consumers to take the “Pepsi Challenge.” Consumers
were asked to decide which of two sodas, Coke or Pepsi, they preferred in a blind taste
test. Pepsi was interested in determining what factors played a role in people’s taste
preferences. One of the factors studied was the gender of the consumer. Data on the
percentage of men and women depicting preference for Pepsi were collected. Which of
the following tests will you use to find out if there is any difference in preference
between the different gender groups?
A) McNemar test
B) Paired t test
C) Z test for difference in proportions
D) Wilcoxon rank sum test
Referring to Table 14-16, which of the following assumptions is most
likely violated based on the residual plot for Engine Size?
TABLE 14-16
What are the factors that determine the acceleration time (in sec.)
from 0 to 60 miles per hour of a car? Data on the following variables
for 30 different vehicle models were collected:
Y (Accel Time): Acceleration time in sec.
X1 (Engine Size): c.c.
X2 (Sedan): 1 if the vehicle model is a sedan and 0 otherwise
The regression results using acceleration time as the dependent
variable and the remaining variables as the independent variables are
presented below.
The various residual plots are as shown below.
The coefficient of partial determinations and are 0.3301,
and 0.0594, respectively.
The coefficient of determination for the regression model using each
of the 2 independent variables as the dependent variable and the
other independent variable as independent variables ( ) are,
respectively 0.0077, and 0.0077.
A) Linearity
B) Normality of errors
C) Independence of errors
D) None of the above
Referring to Table 14-2, for these data, what is the estimated coefficient for the number
of economics courses taken, b2?
TABLE 14-2
A professor of industrial relations believes that an individual’s wage rate at a factory (Y)
depends on his performance rating (X1) and the number of economics courses the
employee successfully completed in college (X2). The professor randomly selects 6
workers and collects the following information:
A) 0.616
B) 1.054
C) 6.932
D) 9.103
Suppose the probability of producing a defective light bulb from a production line is the
same over an interval of 90 minutes. Which of the following distributions would you
use to determine the probability that a defective light bulb will be produced in a
15-minute interval?
A) Normal distribution
B) Poisson distribution
C) Uniform distribution
D) Exponential distribution
TABLE 16-11
The manager of a health club has recorded mean attendance in newly introduced step
classes over the last 15 months: 32.1, 39.5, 40.3, 46.0, 65.2, 73.1, 83.7, 106.8, 118.0,
133.1, 163.3, 182.8, 205.6, 249.1, and 263.5. She then used Microsoft Excel to obtain
the following partial output for both a first- and second-order autoregressive model.
SUMMARY OUTPUT – 2nd Order Model
SUMMARY OUTPUT – 1st Order Model
Referring to Table 16-11, using the second-order model, the forecast of mean
attendance for month 17 is ________.
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.
TABLE 16-14
A contractor developed a multiplicative time-series model to forecast the number of
contracts in future quarters, using quarterly data on number of contracts during the
3-year period from 2010 to 2012. The following is the resulting regression equation:
ln = 3.37 + 0.117 X – 0.083 1 + 1.28 2 + 0.617 3
where is the estimated number of contracts in a quarter
X is the coded quarterly value with X = 0 in the first quarter of 2010
1 is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise
2 is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise
3 is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise
Referring to Table 16-14 , the best interpretation of the constant 3.37 in the regression
equation is
A) the fitted value for the first quarter of 2010, prior to seasonal adjustment, is log10
3.37.
B) the fitted value for the first quarter of 2010, after to seasonal adjustment, is log10
3.37.
C) the fitted value for the first quarter of 2010, prior to seasonal adjustment, is 103.37.
D) the fitted value for the first quarter of 2010, after to seasonal adjustment, is 103.37.
TABLE 3-12
Given below are the rating and performance scores of 15 laptop computers.
Referring to Table 3-12, how will you classify the linear relationship between the
performance scores and the rating?
A) weak
B) moderate
C) strong
D) no relationship
The strength of the linear relationship between two numerical variables may be
measured by the
A) scatter plot.
B) coefficient of correlation.
C) slope.
D) Y-intercept.
Referring to Table 14-1, for these data, what is the estimated coefficient for the variable
representing scores on the aptitude test, b2?
TABLE 14-1
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:
A) 0.998
B) 3.103
C) 4.698
D) 21.293
TABLE 18-8
Recently, a university switched to a new type of computer-based registration. The
registrar is concerned with the amount of time students are spending on the computer
registering under the new system. She decides to randomly select 8 students on each of
the 12 days of the registration and determine the time each spends on the computer
registering. The range, mean, and standard deviation of the times required to register are
in the table that follows.
Referring to Table 18-8, an chart is to be used for the time required to register. The
lower control limit for this data set is ________, while the upper control limit is
________.
The cause of variation that can be reduced only by changing the system is ________
cause variation.
TABLE 13-10
The management of a chain electronic store would like to develop a model for
predicting the weekly sales (in thousands of dollars) for individual stores based on the
number of customers who made purchases. A random sample of 12 stores yields the
following results:
Referring to Table 13-10, what is the value of the F test statistic when testing whether
the number of customers who make purchases is a good predictor for weekly sales?
Referring to Table 14-9, the value of adjusted r2 is ________.
TABLE 14-9
You decide to predict gasoline prices in different cities and towns in
the United States for your term project. Your dependent variable is
price of gasoline per gallon and your explanatory variables are per
capita income and the number of <rms that manufacture automobile
parts in and around the city. You collected data of 32 cities and
obtained a regression sum of squares SSR= 122.8821. Your computed
value of standard error of the estimate is 1.9549.
TABLE 5-9
A major hotel chain keeps a record of the number of mishandled bags per 1,000
customers. In a recent year, the hotel chain had 4.06 mishandled bags per 1,000
customers. Assume that the number of mishandled bags has a Poisson distribution.
Referring to Table 5-9, what is the probability that in the next 1,000 customers, the
hotel chain will have more than eight mishandled bags?
Referring to Table 14-17, predict the number of weeks being
unemployed due to a layo- for a worker who is a thirty-year-old and is
a manager.
TABLE 14-17
Given below are results from the regression analysis where the
dependent variable is the number of weeks a worker is unemployed
due to a layo- (Unemploy) and the independent variables are the age
of the worker (Age) and a dummy variable for management position
(Manager: 1 = yes, 0 = no).
The results of the regression analysis are given below:
TABLE 16-4
The number of cases of merlot wine sold by a Paso Robles winery in an 8-year period
follows.
Referring to Table 16-4, exponentially smooth the wine sales with a weight or
smoothing constant of 0.2.
The number of 911 calls in Butte, Montana, has a Poisson distribution with a mean of
10 calls a day. The probability of seven 911 calls in a day is ________.
TABLE 13-10
The management of a chain electronic store would like to develop a model for
predicting the weekly sales (in thousands of dollars) for individual stores based on the
number of customers who made purchases. A random sample of 12 stores yields the
following results:
Referring to Table 13-10, construct a 95% confidence interval for the mean weekly
sales when the number of customers who make purchases is 600.
TABLE 18-7
A supplier of silicone sheets for producers of computer chips wants to evaluate her
manufacturing process. She takes sample sizes of 5 from each day’s output and counts
the number of blemishes on each silicone sheet. The results from 20 days of such
evaluations are presented below.
She also decides that the upper specification limit is 10 blemishes.
Referring to Table 18-7, an R chart is to be constructed for the number of blemishes.
The upper control limit for this data set is ________.