MGT 424 Test 1 | Course Paper

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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 coe,cient of partial determinations and are 0.3301,

and 0.0594, respectively.

The coe,cient 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.

True or False: Referring to Table 14-16, the errors (residuals) appear to

be right-skewed.

TABLE 12-7

Data on the percentage of 200 hotels in each of the three large cities across the world on

whether minibar charges are correctly posted at checkout are given below.

At the 0.05 level of significance, you want to know if there is evidence of a difference

in the proportion of hotels that correctly post minibar charges among the three cities.

True or False: Referring to Table 12-7, the decision made suggests that the 3 cities all

have different proportions of hotels that correctly post minibar charges.

True or False: The difference between the lower limit of a confidence interval and the

point estimate used in constructing the confidence interval is called the sampling error.

TABLE 15-6

Given below are results from the regression analysis on 40 observations where the

dependent variable is the number of weeks a worker is unemployed due to a layoff (Y)

and the independent variables are the age of the worker (X1), the number of years of

education received (X2), the number of years at the previous job (X3), a dummy variable

for marital status (X4: 1 = married, 0 = otherwise), a dummy variable for head of

household (X5: 1 = yes, 0 = no) and a dummy variable for management position (X6: 1

= yes, 0 = no).

The coefficient of multiple determination ( ) for the regression model using each of

the 6 variables Xj as the dependent variable and all other X variables as independent

variables are, respectively, 0.2628, 0.1240, 0.2404, 0.3510, 0.3342 and 0.0993.

The partial results from best-subset regression are given below:

True or False: Referring to Table 15-6, the model that includes X1, X3, X5 and X6 should

be among the appropriate models using the Mallow’s Cp statistic.

TABLE 11-3

As part of an evaluation program, a sporting goods retailer wanted to compare the

downhill coasting speeds of 4 brands of bicycles. She took 3 of each brand and

determined their maximum downhill speeds. The results are presented in miles per hour

in the table below.

True or False: Referring to Table 11-3, the test is valid only if the population of speeds

is normally distributed.

True or False: A process capability is estimated by the percentage of product or service

that fall outside the specification limits.

True or False: The question “Is your household income last year somewhere between

$50,000 and $100,000?” will most likely result in coverage error.

True or False: 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, we can conclude that, holding constant the effect of

the other independent variables, the number of years of education received has no

impact on the mean number of weeks a worker is unemployed due to a layoff at a 1%

level of significance if all we have is the information of the 95% confidence interval

estimate forÎ²2.

True or False: When using the X2 tests for independence, you should be aware that

expected frequencies that are too small will lead to a large Type I error.

True or False: As a population becomes large, it is usually better to obtain statistical

information from the entire population.

TABLE 8-10

A sales and marketing management magazine conducted a survey on salespeople

cheating on their expense reports and other unethical conduct. In the survey on 200

managers, 58% of the managers have caught salespeople cheating on an expense report,

50% have caught salespeople working a second job on company time, 22% have caught

salespeople listing a ‘strip bar” as a restaurant on an expense report, and 19% have

caught salespeople giving a kickback to a customer.

True or False: Referring to Table 8-10, we are 95% confident that the population mean

number of managers who have caught salespeople cheating on an expense report is

between 0.5116 to 0.6484.

Referring to Table 14-13, the 5tted model for predicting demand in

San Francisco is ________.

TABLE 14-13

An econometrician is interested in evaluating the relationship of

demand for building materials to mortgage rates in Los Angeles and

San Francisco. He believes that the appropriate model is

Y = 10 + 5X1 + 8X2

where X1 = mortgage rate in %

X2 = 1 if SF, 0 if LA

Y = demand in $100 per capita

A) 10 + 5X1

B) 10 + 13X1

C) 15 + 8X2

D) 18 + 5X1

TABLE 9-2

A student claims that he can correctly identify whether a person is a business major or

an agriculture major by the way the person dresses. Suppose in actuality that if someone

is a business major, he can correctly identify that person as a business major 87% of the

time. When a person is an agriculture major, the student will incorrectly identify that

person as a business major 16% of the time. Presented with one person and asked to

identify the major of this person (who is either a business or an agriculture major), he

considers this to be a hypothesis test with the null hypothesis being that the person is a

business major and the alternative that the person is an agriculture major.

Referring to Table 9-2, what is the value of ?

A) 0.13

B) 0.16

C) 0.84

D) 0.87

Which of the following is not part of the DMAIC process in Six Sigma management?

A) Define

B) Do

C) Analyze

D) Control

The director of a training program wanted to know if a one-week orientation would

change the perception of potential clients who would perceive the program as being

good. He collected information on the number of clients who would rate the program as

being good before and after the orientation. Which of the following tests will be the

most appropriate?

A) Ï‡2 test for proportions

B) McNemar test

C) Wilcoxon rank sum test

D) Tukey-Kramer procedure

TABLE 2-3

Every spring semester, the School of Business coordinates a luncheon with local

business leaders 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.

Referring to the histogram from Table 2-3, if all the tickets purchased were used, how

many guests attended the luncheon?

A) 4

B) 152

C) 275

D) 388

You have created a 95% confidence interval for Î¼ with the result 10 15. What

decision will you make if we test H0 : = 16 versus H1 : â‰ 16 at = 0.01?

A) Reject H0 in favor of H1.

B) Do not reject H0 in favor of H1.

C) Fail to reject H0 in favor of H1.

D) You cannot tell what our decision will be from the information given.

In a local cellular phone area, company A accounts for 60% of the cellular phone

market, while company B accounts for the remaining 40% of the market. Of the cellular

calls made with company A, 1% of the calls will have some sort of interference, while

2% of the cellular calls with company B will have interference. If a cellular call is

selected at random and has interference, what is the probability that it was with

company A?

A) 0.071

B) 0.429

C) 0.571

D) It cannot be determined.

An airline wants to select a computer software package for its reservation system. Four

software packages (1, 2, 3, and 4) are commercially available. An experiment is set up

in which each package is used to make reservations for 5 randomly selected weeks and

data on the number of passengers that are bumped over a month are collected. (A total

of 20 weeks was included in the experiment.) The variance on the number of passengers

that are bumped is found to be roughly the same for the 4 packages. Which of the

following tests will be the most appropriate to find out if the mean number of

passengers being bumped over a month is the same across the 4 packages?

A) Paired t test

B) Pooled-variance t test

C) One-way ANOVA F test for differences among more than two means

D) Two-way ANOVA F test for interaction effect

Referring to Table 14-3, one economy in the sample had an aggregate consumption

level of $4 billion, a GDP of $6 billion, and an aggregate price level of 200. What is the

residual for this data point?

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.

A) $4.39 billion

B) $0.39 billion

C) -$0.39 billion

D) -$1.33 billion

Referring to Table 14-4, what are the residual degrees of freedom that are missing from

the output?

TABLE 14-4

A real estate builder wishes to determine how house size (House) is influenced by

family income (Income) and family size (Size). House size is measured in hundreds of

square feet and income is measured in thousands of dollars. The builder randomly

selected 50 families and ran the multiple regression. Partial Microsoft Excel output is

provided below:

Also SSR (X1âˆ£ X2) = 36400.6326 and SSR (X2âˆ£ X1) = 3297.7917

A) 2

B) 47

C) 49

D) 50

A buyer for a manufacturing plant suspects that his primary supplier of raw materials is

overcharging. In order to determine if his suspicion is correct, he contacts a second

supplier and asks for the prices on various identical materials. He wants to compare

these prices with those of his primary supplier. He collected data on 6 different

materials from both suppliers. He believes that the differences are normally distributed.

Which of the following tests will be the most appropriate?

A) Pooled-variance t test

B) Paired t test

C) Wilcoxon rank sum test

D) McNemar test

Which of the following best measures the ability of a process to consistently meet

specified customer-driven requirements?

A) Process capability

B) Specification limits

C) Upper control limit

D) Lower control limit

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 possible responses to the question “Are you 1. Currently

employed,

2. Unemployed but actively looking for job, 3. Unemployed and quit looking for job?”

result in

A) a nominal scale variable.

B) an ordinal scale variable.

C) an interval scale variable.

D) a ratio scale variable.

Which of the following sampling methods is a probability sample?

A) convenience sample

B) quota sample

C) stratified sample

D) judgment sample

A university system enrolling hundreds of thousands of students is considering a change

in the way students pay for their education. Currently, the students pay $400 per credit

hour. The university system administrators are contemplating charging each student a

set fee of $7,000 per quarter, regardless of how many credit hours each takes. To see if

this proposal would be economically feasible, the administrators would like to know

how many credit hours, on the average, each student takes per quarter. A random

sample of 250 students yields a mean of 14.1 credit hours per quarter and a standard

deviation of 2.3 credit hours per quarter. Suppose the administration wanted to estimate

the mean to within 0.1 hours at 95% reliability and assumed that the sample standard

deviation provided a good estimate for the population standard deviation. How large a

total sample would they need to take?

TABLE 4-8

According to the record of the registrar’s office at a state university, 35% of the students

are freshman, 25% are sophomore, 16% are junior and the rest are senior. Among the

freshmen, sophomores, juniors and seniors, the portion of students who live in the

dormitory are, respectively, 80%, 60%, 30% and 20%.

Referring to Table 4-8, what is the probability that a randomly selected student is a

sophomore who does not live in a dormitory?

The true length of boards cut at a mill with a listed length of 10 feet is normally

distributed with a mean of 123 inches and a standard deviation of 1 inch. What

proportion of the boards will be between 121 and 124 inches?

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, what is the opportunity loss of spending 8 hours per week on

average studying for the exam when the exam turns out to be difficult?

Referring to Table 14-16, ________ of the variation in Accel Time can be

explained by the two independent variables.