Deck 16: Introduction to Data Mining

Question 1

According to the output below, which of the following statement is true about the correlation between stock price and earnings per share (EPS)?

A) The correlation is negative.
B) The correlation is not significantly different from zero.
C) The correlation is positive and significantly different from zero.
D) The correlation is positive but not significantly different from zero.
E) Cannot be determined from the information given.

Answer 1

The correlation is positive and significantly different from zero.

Question 2

Data were collected for a sample of 12 pharmacists to determine if years of experience and salary are related. Based on the results below, the calculated t-
Statistic to test whether the regression slope is significant is

A) 10.99
B) 47.97
C) 31.2
D) 6.93
E) 5.58485

Answer 2

6.93

Question 3

In a regression analysis predicting tourism revenue ($billion) using number of foreign visitors (million), the P-value for the calculated test statistic is 0.006. At the 0.05
Level of significance we

A) reject the null hypothesis.
B) do not reject the null hypothesis.
C) conclude that the number of foreign visitors is significant in explaining tourism
Revenue.
D) Both A and C.
E) Both B and C.

Answer 3

Both A and C.

Question 4

According to the results below, what is the correlation between stock price and EPS?

A) -0.975
B) 0.906
C) 0.950
D) 0.975
E) Cannot be determined from the information given.

Question 5

Based on the regression output and residual plot below, which of the following is true?
Regression Analysis: Technology Adoption versus Time
Technology Adoption = - 11.9 +
3)37 Time
S = 6.30783 R-Sq = 82.5%
The regression equation is: Durbin-Watson statistic = 0.278634

A) The linear model explains 82.5 % of the variability in technology adoption.
B) The linear model is appropriate.
C) The linear model is not appropriate.
D) Both A and B.
E) Both A and C.

Question 6

From the plots of residuals shown below, which assumption appears to be violated?

A) Equal Variance
B) Linearity
C) Normality
D) Independence
E) None; all appear to be satisfied.

Question 7

According to the partial regression analysis output below, what is the t-statistic to test whether the regression slope is significant?

A) 6.20
B) 13.88
C) 0.07917
D) 2.58307
E) 3.73

Question 8

Regression analysis was performed to develop a model for predicting a firm's Price- Earnings Ratio (PE) based on Growth Rate, Profit Margin, and whether or not the
Firm is Green (1 = Yes, 0 = No). Based on the F-statistic of 26.48 which has a p-value
Of 0.000, we can conclude at α = .05 that

A) the regression equation is not significant.
B) all independent variables in the model are significant.
C) the regression equation is significant.
D) none of the independent variables in the model are significant.
E) both B and C.

Question 9

Data were collected for a sample of 12 pharmacists to determine if years of experience and salary are related. A regression was run with the dependent variable
Salary (thousands of dollars) and independent variable Experience (years). Suppose
The P-value associated with the calculated t-statistic is < .001. At the .05 level of
Significance we

A) reject the null hypothesis.
B) do not reject the null hypothesis.
C) conclude that years of experience is significant in explaining pharmacists' salary.
D) Both A and C.
E) Both B and C.

Question 10

Using this regression equation: Salary = 37.2 + 1.49 Years' Experience to predict salary for pharmacists with 10 years of experience gives the following results. Which
Of the following is true?

A) 95% of pharmacists with 10 years of experience earn between $38,960 and
$65,130.
B) 95% of pharmacists with 10 years of experience earn between $48,010 and
$56,080.
C) We are 95% confident that a particular pharmacist who has 10 years of experience
Earns between $38,960 and $65,130.
D) We are 95% confident that a particular pharmacist who has 10 years of experience
Earns between $48,010 and $56,080
E) 95% of pharmacists with 10 years experience on average earn between $48,010
And $56,080.

Question 11

According to the regression analysis output below, how much of the variability in tourism revenue is accounted for by the number of foreign visitors?

A) 63.4 %
B) 13.8 %
C) 2.58 billion $
D) 21.464 %
E) 3.73 billion $

Question 12

A regression model: PE = 8.04 + 0.747 Growth Rate + 0.0516 Profit Margin + 2.09 Green was developed to predict a firm's Price-Earnings Ratio (PE) using
Growth Rate, Profit Margin, and whether the firm is Green (1 = Yes, 0 = No). Which
Of the following is the correct interpretation for the regression coefficient of Green?

A) The regression coefficient indicates that the PE ratio of a firm that is green will,
On average, be 2.09 higher than a firm that is not green with the same growth rate
And profit margin.
B) The regression coefficient indicates that the PE ratio of a firm that is green will,
On average, be 2.09 lower than a firm that is not green with the same growth rate
And profit margin.
C) The regression coefficient indicates that the PE ratio of a firm that is green will,
On average, be 2.09 times higher than a firm that is not green with the same
Growth rate and profit margin.
D) The regression coefficient indicates that the PE ratio of a firm that is green will,
On average, be 2.09 times lower than a firm that is not green with the same growth
Rate and profit margin.
E) The regression coefficient is not significantly different from zero.

Question 13

If we were interested in using regression methods to predict the tourism revenue for a particular country that had 30 million foreign visitors we should

A) construct a confidence interval using the regression equation.
B) construct a predication interval using the regression equation.
C) use the correlation.
D) use the standard error.
E) None of these.

Question 14

A patient is injected with the drug and the concentration (units/cc) in the patient's blood is measured every hour for seven hours. Re-expressing these data result in the
Following model and residual plot. What is true about the predicted concentration
Level after 10 hours has elapsed?
Log(Concentration) = 1.79 - 0.169 Time Elapsed.
S = 0.00565191 R-Sq = 100.0%

A) The predicted value is 1.259 units/cc.
B) This value is considered an extrapolation.
C) This value is accurate because R2 = 100%.
D) Both A and B.
E) All of the above.

Question 15

Data are collected on the number of foreign visitors to a country (million) and total tourism revenue ($billion) for a sample of 10 countries. According to the following
Output, what is standard error of the slope for this estimated regression equation? S = 2.58307 R-Sq = 63.4%

A) 2.58307
B) 3.462
C) 0.07917
D) 6.672
E) 0.29497

Question 16

A patient is injected with the drug and the concentration (units/cc) in the patient's blood is measured every hour for seven hours. Based on the linear regression output
Below, which of the following is true?
Regression Analysis:
The regression equation is
Concentration = 41.3 - 6.00 Time Elapsed
S = 4.72077 R-Sq = 90.0%
Concentration versus Time Elapsed

A) The linear model is appropriate given that it explains 90% of the variability in
Blood concentration levels of the drug.
B) If the observed pattern continues into the future, this model will underestimate the
Concentration level after 10 hours has elapsed because the linear model is not
Appropriate.
C) If the observed pattern continues into the future, this model will overestimate the
Concentration level after 10 hours has elapsed because the linear model is not
Appropriate.
D) Both A and B.
E) Both A and C.

Question 17

Data were collected for a sample of 12 pharmacists to determine if years of experience and salary are related. Based on the results below, the standard error of
The slope for this estimated regression equation is

A) 3.381
B) 0.2149
C) 5.58485
D) 82.8
E) 1.4882

Question 18

Based on the output below from regression analysis performed to develop a model for predicting a firm's Price-Earnings Ratio (PE) based on Growth Rate, Profit Margin,
And whether or not the firm is Green (1 = Yes, 0 = No), we can conclude (α = .05)
That

A) Growth Rate is not a significant variable in predicting a firm's PE ratio.
B) Profit Margin is a significant variable in predicting a firm's PE ratio.
C) The regression coefficient associated with Growth Rate is not significantly
Different from zero.
D) Whether or not a firm is Green is significant in predicting its PE ratio.
E) The regression coefficient associated with Profit Margin is significantly different
From zero.

Question 19

A least squares estimated regression line has been fitted to a set of data and the resulting residual plot is shown. Which is true?

A) The linear model is appropriate.
B) The linear model is poor because some residuals are large.
C) The linear model is poor because the correlation is near 0.
D) A curved model would be better.
E) A transformation of the data is required.

Question 20

Data were collected for a sample of 12 pharmacists to determine if years of experience and salary are related. Based on the output below, how much of the
Variability in pharmacists' salary is accounted for by years of experience?

A) 82.8 %
B) 47.97 %
C) 5.58485 thousand dollars
D) 10.99 %
E) 98.9 %

Question 21

Use the following information
Suppose data mining is employed on telecommunication company data warehouse in order to answer the following questions. On the line to the right of each, indicate whether these involve a classification (C) or regression (R) problem.
How much does a customer spend on all household communication-related
expenditures? ____

Question 22

According to the multiple regression model to predict the job performance of new hires based on age, GPA and gender (female = 1 and male = 0) shown below, how
Much of the variability in Job Performance is explained by the model?

A) 30.33 %
B) 77.7 %
C) 5.56 %
D) 60.76 %
E) Cannot be determined.

Question 23

From its plot of residuals versus fitted

A) Equal Variance
B) Linearity
C) Normality
D) Independence
E) None; all appear to be satisfied.

Question 24

Use the following information
Suppose data mining is employed on telecommunication company data warehouse in order to answer the following questions. On the line to the right of each, indicate whether these involve a classification (C) or regression (R) problem.
Whether or not a customer would be interested in flexible cable TV plans (subscribe to different channels on different days/times)? ____

Question 25

The model can be used to predict the breaking strength (pounds) of a rope from its diameter (inches). According to this model, how much force should a
Rope one-half inch in diameter withstand?

A) 484 pounds
B) 16 pounds
C) 22 pounds
D) 256 pounds
E) 4.7 pounds

Question 26

Based on the regression output shown below, which of the following statements is true?
The regression equation is
Price (cents) = 128 + 1.08 Time
Predictor Coef SE Coef T P
Constant 128.112 2.092 61.25 0.000
Time 1.0782 0.1407 7.66 0.000
S = 5.07299 R-Sq = 71.9%
Durbin-Watson statistic = 0.244822

A) The regression slope is significantly different from zero.
B) The model explains 71.9% of the variability in heating oil prices.
C) The linear model is appropriate.
D) Both A and B.
E) All of the above.

Question 27

According to the following regression analysis, the correlation between average annual cash bonus and average annual pay using α = 0.05 is

A) not significantly different from zero.
B) negative but not significantly different from zero.
C) positive and significantly different from zero.
D) negative and significantly different from zero.
E) Cannot be determined from the information given.

Question 28

The regression equation to predict the job performance of new hires based on age, GPA and gender (female = 1 and male = 0) is Job Performance = -60.8 + 4.80
Age + 1.44 GPA + 9.06 Gender. Which of the following is the correct
Interpretation for the regression coefficient of Gender?

A) The regression coefficient indicates that the job performance score for a female
Will, on average, be 9.06 points higher than for males of the same age and GPA.
B) The regression coefficient indicates that the job performance score for a female
Will, on average, be 9.06 points lower than for males of the same age and GPA.
C) The regression coefficient indicates that the job performance score for a female
Will, on average, be 9.06 times higher than for males.
D) The regression coefficient indicates that the job performance score for a female
Will, on average, be 9.06 times lower than for males.
E) The regression coefficient is not significantly different from zero.

Question 29

Which of the following statements about a residual plot is true?

A) A curved pattern indicates nonlinear association between the variables.
B) A pattern of increasing spread indicates the predicted values become less reliable
As the explanatory variable increases.
C) If all of the residuals are very small, the model will predict accurately.
D) It should not be used if the regression results are not significant.
E) It cannot be used to analyze linear association.

Question 30

Which statement about influential points is true?

A) Removal of an influential point changes the regression line.
B) A high leverage point is always influential.
C) Influential points have large residuals.
D) All outliers are influential.
E) None of these.

Question 31

Disparate databases that include demographic and transactional variables merged together are referred to as

A) Data storage bins
B) Data mines
C) OLAP
D) CRISP
E) Data warehouses

Question 32

Using the following regression analysis of the relationship between the size of cash bonuses and pay scale, find the correlation between average annual cash bonus and
Average annual pay?

A) -0.540
B) -0.223
C) 0.108
D) 0.472
E) Cannot be determined from the information given.

Question 33

Use the following information
Suppose data mining is employed on telecommunication company data warehouse in order to answer the following questions. On the line to the right of each, indicate whether these involve a classification (C) or regression (R) problem.
Whether or not a customer would be interested in wireless internet capabilities? ____

Question 34

The results of a multiple regression model to predict the job performance of new hires based on age, GPA and gender (female = 1 and male = 0 are shown below. At α =
)05 we can conclude that S = 5.56691 R-Sq = 77.7%

A) Age is not a significant variable in predicting job performance.
B) GPA is a significant variable in predicting job performance.
C) The regression coefficient associated with GPA is significantly different from
Zero.
D) Gender is a significant variable in predicting job performance.
E) The regression coefficient associated with Age is not significantly different from
Zero.

Question 35

A linear model is fit to estimate the diameter of maple trees based on age. According to the scatterplot and residual plots shown below, which of the following is true?

A) Assuming the pattern continues into the future, if we use this model to predict the
Diameter of a maple tree that is 50 years old it would be too low.
B) Assuming the pattern continues into the future, if we use this model to predict the
Diameter of a maple tree that is 50 years old it would be too high.
C) Re-expressing these data by taking the logarithm of age would improve this
Model.
D) Both A and B.
E) Both B and C.

Question 36

A farmer has increased his wheat production by about the same amount each year. His most useful predictive model is most probably

A) exponential.
B) linear.
C) logarithmic.
D) power.
E) quadratic.

Question 37

The results of a multiple regression model to predict the job performance of new hires based on age, GPA and gender (female = 1 and male = 0) resulted in an F-statistic of
30)23 and associated p-value of 0.000, we can conclude at α = .05 that

A) the regression equation is not significant.
B) all independent variables in the model are significant.
C) the regression equation is significant.
D) none of the independent variables in the model are significant.
E) both B and C.

Question 38

Use the following information for questions 1 thorough 5:
Below is a list of a few variables for which data were collected from various
telecommunication companies. On the line to the right of each variable, identify whether
it is transactional (T) or a demographic (D).

Question 39

According to the residual plot for a linear regression model shown to the right, the linear model

A) okay because the same number of points is above the
Line as below it.
B) okay because the association between the two
Variables is fairly strong.
C) no good because the correlation is near 0.
D) no good because some residuals are large.
E) no good because of the curve in the residuals.

Question 40

According to the residual plots shown below, which linear regression assumptions appear to be violated?

A) Linearity
B) Normality
C) Equal Variance
D) Both A and B
E) All of the above

Question 41

In a data warehouse, which of the following variables is/are demographic?

A) Age.
B) Occupation.
C) Amount spent on organic food products.
D) Both A and B.
E) All of the above.

Question 42

Which is not a phase of the data mining process?

A) Business understanding.
B) Data preparation.
C) Modeling.
D) Deployment.
E) None of the above.

Question 43

In a data warehouse, which of the following variable(s) is/are demographic?

A) Number of magazine subscriptions.
B) Monthly expenditures on cleaning supplies.
C) Homeowner (Yes or No).
D) Both A and B.
E) All of the above.

Question 44

Use the following information
Suppose data mining is employed on supermarket chains and travel industry dataBwarehouse in order to answer the following questions. On the line to the right, indicate whether these involve a classification (C) or regression (R) problem.
Whether or not a customer is interested in eco-friendly travel products? ____

Question 45

Explain how data mining differs from statistical inference.

Question 46

Describe the phases of the data mining process.

Question 47

Suppose data mining is employed to answer the following questions. Which is considered a regression problem?

A) Whether or not a customer would be interested in wireless internet capabilities?
B) How much does a customer spend on all household communication-related
Expenditures?
C) Whether or not a customer would be interested in flexible cable TV plans
(subscribe to different channels on different days/times)?
D) Both A and B.
E) All of the above.

Question 48

In a data warehouse, which of the following variables is/are demographic?

A) Number of residents in household.
B) Gender of head of household.
C) Monthly electricity usage.
D) Both A and B.
E) All of the above.

Question 49

In a data warehouse, which of the following variable(s) is/are transactional?

A) Annual expenditures on garden supplies.
B) Number of children in household.
C) Household income.
D) Both A and B.
E) All of the above.

Question 50

Suppose the goal of data mining using this data warehouse was to predict whether a household's telecommunication needs will increase, decrease or stay the same over the next year. What technique might be most appropriate for achieving this goal?

Question 51

Use the following information
Suppose data mining is employed on supermarket chains and travel industry dataBwarehouse in order to answer the following questions. On the line to the right, indicate whether these involve a classification (C) or regression (R) problem.
How much a customer spends annually on travel related products? ____

Question 52

Use the following information
Suppose data mining is employed on supermarket chains and travel industry dataBwarehouse in order to answer the following questions. On the line to the right, indicate whether these involve a classification (C) or regression (R) problem.
How much a customer spends annually on international specialty food items? ____

Question 53

Suppose the goal of data mining in a data warehouse was to predict whether a household's telecommunication needs will increase, decrease or stay the same over
The next year. What technique is most appropriate for achieving this goal?

A) Neural network.
B) Supervised problem.
C) Tree model.
D) Nodal network.
E) None of the above.

Question 54

Popular data mining tools inspired by models that tried to mimic the function of the brain are known as

A) Tree models.
B) Supervised problems.
C) Neural networks.
D) Nodal network.
E) None of the above.

Question 55

Use the following information for questions
Scanner data gathered from various supermarket chains were merged with data from the
travel industry (e.g., airlines, hotels, etc) into one data warehouse. Below is a list of a
few variables for which data were collected. On the line to the right, indicate whether the
variable is transactional (T) or demographic (D).

Question 56

Which is considered a data mining classification problem?

A) Whether or not a customer is interested in eco-friendly travel products?
B) How much a customer spends annually on travel related products?
C) How much a customer spends annually on international specialty food items?
D) Both B and C.
E) All of the above.

Question 57

In a data warehouse, which of the following variables is/are transactional?

A) Amount spent on organic food products.
B) Number of international flights taken annually.
C) Types of eco-friendly products purchased.
D) Both A and B.
E) All of the above.

Question 58

Data not used in building the model but used to evaluate the performance of the model is known as

A) the terminal node.
B) the test set.
C) meta data.
D) the training set.
E) None of the above.

Question 59

Suppose the goal of data mining using this data warehouse was to predict whether a customer's expenditures on international specialty food items would increase, decrease or stay the same in the next year. What technique might be most appropriate for achieving this goal?

Question 60

In a data warehouse, which of the following variables is/are transactional?

A) Type of cell phone plan.
B) Zip code.
C) Household income.
D) Both A and B.
E) All of the above.

Question 61

Suppose data mining is used to determine whether or not a household subscribes to magazines about home and garden. In data mining this is referred to as what type of
Problem?

A) Regression.
B) Transactional.
C) Unsupervised.
D) Classification.
E) None of the above.

Question 62

Suppose the goal of data mining using in a data warehouse is to predict whether a customer's expenditures on international specialty food items would increase,
Decrease or stay the same in the next year. What technique might be most appropriate
For achieving this goal?

A) Neural network.
B) Unsupervised problem.
C) Tree model.
D) Nodal network.
E) None of the above.

Question 63

Suppose data mining is used to determine how important it is for a customer to purchase a vehicle with a very low carbon footprint. In data mining this is referred to
As what type of problem?

A) Regression.
B) Transactional.
C) Unsupervised.
D) Classification.
E) None of the above.

Question 64

Information about variables, such as variable definitions as well as how and when data were collected, is collectively called

A) superdata.
B) metadata.
C) extradata.
D) cases.
E) none of the above.

Question 65

In a data warehouse, which of the following variable(s) is/are transactional?

A) Gender.
B) Homeowner (Yes or No).
C) Purchase price of a vehicle.
D) Both B and C.
E) None of the above.

Question 66

Suppose data mining is used to determine how much a customer spends annually on energy efficient products. In data mining this is referred to as what type of problem?

A) Regression.
B) Transactional.
C) Unsupervised.
D) Classification.
E) None of the above.

Question 67

Data used in a supervised problem to build the predictive model is known as

A) the terminal node.
B) the test set.
C) meta data.
D) the training set.
E) none of the above.

Question 68

Suppose data mining is used to determine whether or not a customer would purchase a hybrid vehicle. In data mining this is referred to as what type of problem?

A) Regression.
B) Transactional.
C) Unsupervised.
D) Classification.
E) None of the above.