Question 1

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

Accepted Answer

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

Question 2

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? Regression Analysis: Cash Bonus versus Pay
The regression equation is: Cash Bonus $= - 4877 + 0.245$ Pay
$\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & T & \text { P } \ \text { Constant } & - 4877 & 9106 & - 0.54 & 0.599 \ \text { Pay } & 0.2453 & 0.1079 & 2.27 & 0.036 \end{array}$
$$\mathrm { S } = 13188.6 \quad \mathrm { R } - \mathrm { Sq } = 22.3 \%$$

Accepted Answer

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

Question 3

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? ____

Accepted Answer

$\underline { \mathrm { C } }$

Question 4

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?

Accepted Answer

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

Question 5

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

Accepted Answer

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. 
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 6

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%

Accepted Answer

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. 
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 7

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). 
1. Amount spent on organic food products____
2. Number of international flights taken annually____
3. Age______
4. Types of eco-friendly products purchased__________
5. Occupation______

Accepted Answer

1. Amount spent on organic foo

Question 8

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

Accepted Answer

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. 
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 9

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

Accepted Answer

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. 
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 10

From its plot of residuals versus fitted

Accepted Answer

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

Question 11

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 The regression equation is
$\mathrm { Job }$ Performance $= - 60.8 + 4.80 \mathrm { Age } + 1.44 \mathrm { GPA } + 9.06$ Gender
$\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \ \text { Constant } & - 60.76 & 22.49 & - 2.70 & 0.012 \ \text { Age } & 4.802 & 1.177 & 4.08 & 0.000 \ \text { GPA } & 1.443 & 2.379 & 0.61 & 0.549 \ \text { Gender } & 9.060 & 2.314 & 3.92 & 0.001 \ \mathbf { S } = 5.56691 & \mathbf { R } - \mathrm { Sq } = & 77.7 \% \end{array}$

Accepted Answer

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 fromZero. 
D)  Gender is a significant variable in predicting job performance. 
E)  The regression coefficient associated with Age is not significantly different fromZero. 
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 fromZero. 
D)  Gender is a significant variable in predicting job performance. 
E)  The regression coefficient associated with Age is not significantly different fromZero.

Question 12

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

Accepted Answer

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

Question 13

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

Accepted Answer

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. 
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 14

Describe the phases of the data mining process.

Accepted Answer

Business understanding, data u

Question 15

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

Accepted Answer

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

Question 16

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

Accepted Answer

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. 
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 17

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?

Accepted Answer

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

Question 18

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

Accepted Answer

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. 
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 19

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

Accepted Answer

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. 
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.

Question 20

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? The regression equation is
Job Performance $= - 60.8 + 4.80 \mathrm { Age } + 1.44 \mathrm { GPA } + 9.06$ Gender
$\begin{array} { l r r r r } \text { Predictor } & \text { Coef } & \text { SE Coef } & \text { T } & \text { P } \ \text { Constant } & - 60.76 & 22.49 & - 2.70 & 0.012 \ \text { Age } & 4.802 & 1.177 & 4.08 & 0.000 \ \text { GPA } & 1.443 & 2.379 & 0.61 & 0.549 \ \text { Gender } & 9.060 & 2.314 & 3.92 & 0.001 \end{array}$
$$S = 5.56691 \quad \mathrm { R } - \mathrm { Sq } = 77.7 \%$$

Accepted Answer

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

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

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?

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

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

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

From its plot of residuals versus fitted

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

Describe the phases of the data mining process.

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

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

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?

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

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

Data and Decisions

Displaying and Describing Categorical Data

Displaying and Describing Quantitative Data

Correlation and Linear Regression

Randomness and Probability

Random Variables and Probability Models

The Normal and Other Continuous Distributions

Surveys and Sampling

Sampling Distributions and Confidence Intervals for Proportions

Testing Hypotheses About Proportions

Confidence Intervals and Hypothesis Tests for Means

Comparing Two Means

Inference for Counts: Chi-Square Tests

Inference for Regression

Multiple Regression

Filters

Exam 16: Introduction to Data Mining

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

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?

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

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

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

From its plot of residuals versus fitted

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

Describe the phases of the data mining process.

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

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

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?

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

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

Data and Decisions

Displaying and Describing Categorical Data

Displaying and Describing Quantitative Data

Correlation and Linear Regression

Randomness and Probability

Random Variables and Probability Models

The Normal and Other Continuous Distributions

Surveys and Sampling

Sampling Distributions and Confidence Intervals for Proportions

Testing Hypotheses About Proportions

Confidence Intervals and Hypothesis Tests for Means

Comparing Two Means

Inference for Counts: Chi-Square Tests

Inference for Regression

Multiple Regression

Filters