# A telemarketing company wants to find

22.
A telemarketing company wants to find out if people are more likely to answer the phone between 8pm and 9pm than between 7pm and 8pm. Out of 96 calls between 7pm and 8pm, 72 were answered. Out of 105 calls between 8pm and 9pm, 90 were answered.

Using a one-sided hypothesis test with a 90% confidence level, which of the following statements do these data support?
Source
There is not sufficient evidence that the proportion of people who answer the phone between 8pm and 9pm is greater than the proportion who answer the phone between 7pm and 8pm.
People are more likely to answer the phone between 8pm and 9pm.
Telemarketers should not call at all during the evenings.
People are more likely to answer the phone between 7pm and 8pm.
23.
The regression analysis below relates US annual energy consumption in trillions of BTUs to the independent variable “US Gross Domestic Product (GDP) in trillions of dollars.”

Which of the following is the lowest level at which the independent variable is significant?
Energy Consumption and GDP
Source
0.94
0.10
0.05
0.01

24.
The regression analysis below relates US annual energy consumption in trillions of BTUs to the independent variable “US Gross Domestic Product (GDP) in trillions of dollars.”

The coefficient on the independent variable tells us that:
Energy Consumption and GDP
Source

For every additional trillion dollars of GDP, average energy consumption increased by 3,786 trillion BTUs.
For every additional dollar of GDP, average energy consumption increased by 3,786 trillion BTUs.
For every additional trillion dollars of GDP, average energy consumption increased by 3,786 BTUs.
For every additional trillion BTUs of energy consumption, average GDP increased by \$3,786 trillion.
25.
The regression analysis below relates US annual energy consumption in trillions of BTUs to the independent variable “US Gross Domestic Product (GDP) in trillions of dollars.”

Which of the following statements is true?
Energy Consumption and GDP
Source
The y-intercept of the regression line is 62,695 trillion BTUs.
The x-intercept of the regression line is \$62,695 trillion.
In the event that a thermonuclear war completely halts all economic activity and the US GDP drops to zero, energy consumption will sink to 62,695 trillion BTUs.
None of the above.
26.
The regression analysis below relates US annual energy consumption in trillions of BTUs to the independent variable “US Gross Domestic Product (GDP) in trillions of dollars.”

In a given year, if GDP is \$7.4 trillion, expected energy consumption is:
Energy Consumption and GDP
Source
Around 90,711 trillion BTUs
Around 91,501 trillion BTUs
Around 28,016 trillion BTUs
Around 467,729 trillion BTUs.
27.
The regression analysis below relates US annual energy consumption in trillions of BTUs to the independent variable “US Gross Domestic Product (GDP) in trillions of dollars.”

How much of the variation in energy consumption can be explained by variation in the gross domestic product?
Energy Consumption and GDP
Source
Almost none of the variation in energy consumption can be explained by variation in GDP.
30
The regression analysis below relates US annual energy consumption in trillions of BTUs to the independent variables “US Gross Domestic Product (GDP) in trillions of dollars” and “average gas mileage of all passenger cars in miles per gallon (mpg).”

The coefficient for the independent variable “average car gas mileage (mpg),” -70.50, describes:
Energy Consumption, GDP, and Gas Mileage
Source
The relationship between energy consumption and average car gas mileage, controlling for GDP

The relationship between energy consumption and average car gas mileage, not controlling for GDP.

The relationship between average car gas mileage and GDP, controlling for energy consumption
The relationship between average car gas mileage and GDP, not controlling for energy consumption.
31.
The data table below tabulates a pizza parlor’s advertising expenditures and sales for 8 consecutive quarters. The marketing manager wants to know how much of an impact current advertising will have on sales two quarters from now.

When running a regression with the dependent variable “sales” and the independent variable “advertising lagged by two quarters,” how many data points can she use, given the available data?
Source
Answers: 6, 7, 8 or 9

32.

In a regression analysis, a residual is defined as:
Source
The difference between the actual value and the predicted value of the dependent variable.
The difference between the actual value and the predicted value of the independent variable.
The proportion of the variation in the independent variable that remains unexplained by the variation in the dependent variable.
The proportion of the variation in the dependent variable that remains unexplained by the variation in the independent variable
33.
When comparing two regression analyses that have a different number of independent variables, which of the following should be used to compare the explanatory power of the two regressions?
Source
R-squared.
The correlation coefficient (“Multiple R”).
None of the above
34
Amalgamated Fruits, Vegetables, and Legumes, an agricultural company, breeds the experimental fruit “kiwana.” The company is studying the effects of a new fertilizer on the number of kiwanas per bunch grown on kiwana trees. The regression analysis below relates the number of kiwanas per bunch to the independent dummy variable “fertilizer.”

Based on the regression, which of the following statements may be concluded?
Kiwana Growth and Fertilizer
Source

On average, the use of the new fertilizer increases the number of kiwanas per bunch by 5.25.
The independent dummy variable “fertilizer” is significant at the 0.01 level.
Variation in the independent dummy variable “fertilizer” explains around 53% of the variation in the number of kiwanas per bunch.
None of the above.
35.
In a regression analysis with multiple independent variables, multicollinearity can be caused by:
Source

A strong linear relationship between two or more independent variables.
A strong nonlinear relationship between the dependent variable and one or more independent variables.
A strong heteroskedastic relationship between the dependent variable and one or more independent variables.
None of the above.
36.
Market researcher Ally Nathan is studying the relationships among price, type (classical or steel string), and consumer demand for acoustic guitars. She wants to find the relationship between demand and price, controlling for type.

To determine this relationship, she should:
Source

Run a simple regression of the dependent variable demand on the independent variable price and observe the coefficient on price.
Run a simple regression of the dependent variable demand on the independent variable type and observe the coefficient on type.
Run a multiple regression of the dependent variable demand on the independent variables price and type and observe the coefficient on price.
Run a multiple regression of the dependent variable demand on the independent variables price and type and observe the coefficient on type.
37.
The table below displays data on defect rates at a compact disk (CD) pressing facility. The table includes data on the distribution of CDs that have content errors (missing and/or wrong content), and on the distribution of CDs that have labeling errors.

What is the probability that a randomly selected CD has a content error?
Source

1.00%
0.98%
0.02%
None of the above.

38.
The table below displays data on defect rates at a compact disk (CD) pressing facility. The table includes data on the distribution of CDs that have content errors (missing and/or wrong content), and on the distribution of CDs that have labeling errors.

What is the conditional probability that a CD has no content errors, given that has a labeling error?
Source

97.02%
1.98%
98.00%
None of the above
39.
The table below displays data on defect rates at a compact disk (CD) pressing facility. The table includes data on the distribution of CDs that have content errors (missing and/or wrong content), and on the distribution of CDs that have labeling errors.

Which of the following statements is true?
Source
The fact that a CD has a content error tells us nothing about whether it has a labeling error.
The events of a CD having a content error and a CD having a labeling error are statistically dependent.
The fact that a CD has a labeling error tells us something about whether it has a content error.
None of the above.
40.
The WH meat-packing company must decide whether or not to recall one week’s production of kielbasa due to possible contamination. An outbreak of non-fatal food poisoning may be linked to WH. If so, WH may face a lawsuit. The tree below summarizes the decision.

The EMV of the cost of not issuing a recall is \$80,000. Based on EMV, WH should not issue a recall. If WH chooses to recall, which of the following best describes the WH’s attitude towards this decision?
Source

Risk averse.
Risk neutral.
Risk seeking
Chicken.

41.
The WH meat-packing company must decide whether or not to recall one week’s production of kielbasa due to possible contamination. An outbreak of non-fatal food poisoning may be linked to WH. If so, WH may face a lawsuit. The tree below summarizes the decision.

The EMV of the cost of not issuing a recall is \$80,000. Based on EMV, WH should not issue a recall. An estimated value of a reputation loss is included in the outcome estimate of the lawsuit. If WH is implicated, the firm may face a reputation loss even if no lawsuit is filed. For what values of that reputation loss would issuing the recall be preferable, in terms of EMV?
Source

Higher than \$500,000.
Lower than \$500,000.
Lower than \$44,444
None of the above.
42.
The WH meat-packing company must decide whether or not to recall one week’s production of kielbasa due to possible contamination. An outbreak of non-fatal food poisoning may be linked to WH. If so, WH may face a lawsuit. The tree below summarizes the decision.

The EMV of the cost of not issuing a recall is \$80,000. Based on EMV, the manager should not issue the recall. For what values of p = Prob[WH is implicated] is not recalling the kielbasa preferable to recalling the kielbasa, in terms of EMV?
Source

p < 15%
p > 15%
p < 85%
None of the above.
43.
The WH meat-packing company must decide whether or not to recall one week’s production of kielbasa due to possible contamination. An outbreak of non-fatal food poisoning may be linked to WH. If so, WH may face a lawsuit. The tree below summarizes the decision.

The EMV of the cost of not issuing a recall is \$80,000. Suppose there were a way to know for certain whether WH would be implicated or not. What would be the value of this perfect information?
Source