Question 1

The number of users of free/open source data mining software now exceeds that of users of commercial software versions.

Accepted Answer

A) True 
 B)False  True

Question 2

List five reasons for the growing popularity of data mining in the business world.

Accepted Answer

•More intense competition at the global scale driven by customers' ever-changing needs and wants in an increasingly saturated marketplace
•General recognition of the untapped value hidden in large data sources
•Consolidation and integration of database records, which enables a single view of customers, vendors, transactions, etc.
•Consolidation of databases and other data repositories into a single location in the form of a data warehouse
•The exponential increase in data processing and storage technologies
•Significant reduction in the cost of hardware and software for data storage and processing
•Movement toward the de-massification (conversion of information resources into nonphysical form) of business practices

Question 3

All of the following statements about data mining are true EXCEPT

Accepted Answer

A)  the process aspect means that data mining should be a one-step process to results. 
B)  the novel aspect means that previously unknown patterns are discovered. 
C)  the potentially useful aspect means that results should lead to some business benefit. 
D)  the valid aspect means that the discovered patterns should hold true on new data. 
A)  the process aspect means that data mining should be a one-step process to results. 
B)  the novel aspect means that previously unknown patterns are discovered. 
C)  the potentially useful aspect means that results should lead to some business benefit. 
D)  the valid aspect means that the discovered patterns should hold true on new data. A

Question 4

The data field "ethnic group" can be best described as

Accepted Answer

A)  nominal data. 
B)  interval data. 
C)  ordinal data. 
D)  ratio data. 
A)  nominal data. 
B)  interval data. 
C)  ordinal data. 
D)  ratio data.

Question 5

The basic idea behind a ________ is that it recursively divides a training set until each division consists entirely or primarily of examples from one class.

Accepted Answer

The answer of The basic idea behind a ________ is...

Question 6

While prediction is largely experience and opinion based, ________ is data and model based.

Accepted Answer

The answer of While prediction is largely experience and opinion...

Question 7

Prediction problems where the variables have numeric values are most accurately defined as

Accepted Answer

A)  classifications. 
B)  regressions. 
C)  associations. 
D)  computations. 
A)  classifications. 
B)  regressions. 
C)  associations. 
D)  computations.

Question 8

Understanding customers better has helped Amazon and others become more successful. The understanding comes primarily from

Accepted Answer

A)  collecting data about customers and transactions. 
B)  developing a philosophy that is data analytics-centric. 
C)  analyzing the vast data amounts routinely collected. 
D)  asking the customers what they want. 
A)  collecting data about customers and transactions. 
B)  developing a philosophy that is data analytics-centric. 
C)  analyzing the vast data amounts routinely collected. 
D)  asking the customers what they want.

Question 9

In the Cabela's case study, what types of models helped the company understand the value of customers, using a five-point scale?

Accepted Answer

A)  reporting and association models 
B)  simulation and geographical models 
C)  simulation and regression models 
D)  clustering and association models 
A)  reporting and association models 
B)  simulation and geographical models 
C)  simulation and regression models 
D)  clustering and association models

Question 10

Which broad area of data mining applications partitions a collection of objects into natural groupings with similar features?

Accepted Answer

A)  associations 
B)  visualization 
C)  classification 
D)  clustering 
A)  associations 
B)  visualization 
C)  classification 
D)  clustering

Question 11

In lessons learned from the Target case, what legal warnings would you give another retailer using data mining for marketing?

Accepted Answer

If you look at this practice from a lega

Question 12

In data mining, finding an affinity of two products to be commonly together in a shopping cart is known as

Accepted Answer

A)  association rule mining. 
B)  cluster analysis. 
C)  decision trees. 
D)  artificial neural networks. 
A)  association rule mining. 
B)  cluster analysis. 
C)  decision trees. 
D)  artificial neural networks.

Question 13

When a problem has many attributes that impact the classification of different patterns, decision trees may be a useful approach.

Accepted Answer

A) True 
 B)False

Question 14

Data that is collected, stored, and analyzed in data mining is often private and personal. There is no way to maintain individuals' privacy other than being very careful about physical data security.

Accepted Answer

A) True 
 B)False

Question 15

Describe cluster analysis and some of its applications.

Accepted Answer

Cluster analysis is an exploratory data

Question 16

In the Memphis Police Department case study, predictive analytics helped to identify the best schedule for officers in order to pay the least overtime.

Accepted Answer

A) True 
 B)False

Question 17

What are the differences between nominal, ordinal, interval and ratio data? Give examples.

Accepted Answer

•Nominal data contain measurement

Question 18

In the opening vignette, Cabela's uses SAS data mining tools to create ________ models to optimize customer selection for all customer contacts.

Accepted Answer

The answer of In the opening vignette, Cabela's uses SAS...

Question 19

List six common data mining mistakes.

Accepted Answer

•Selecting the wrong problem for data mi

Question 20

What does the robustness of a data mining method refer to?

Accepted Answer

A)  its ability to predict the outcome of a previously unknown data set accurately 
B)  its speed of computation and computational costs in using the mode 
C)  its ability to construct a prediction model efficiently given a large amount of data 
D)  its ability to overcome noisy data to make somewhat accurate predictions 
A)  its ability to predict the outcome of a previously unknown data set accurately 
B)  its speed of computation and computational costs in using the mode 
C)  its ability to construct a prediction model efficiently given a large amount of data 
D)  its ability to overcome noisy data to make somewhat accurate predictions

The number of users of free/open source data mining software now exceeds that of users of commercial software versions.

List five reasons for the growing popularity of data mining in the business world.

All of the following statements about data mining are true EXCEPT

The data field "ethnic group" can be best described as

The basic idea behind a ________ is that it recursively divides a training set until each division consists entirely or primarily of examples from one class.

While prediction is largely experience and opinion based, ________ is data and model based.

Prediction problems where the variables have numeric values are most accurately defined as

Understanding customers better has helped Amazon and others become more successful. The understanding comes primarily from

In the Cabela's case study, what types of models helped the company understand the value of customers, using a five-point scale?

Which broad area of data mining applications partitions a collection of objects into natural groupings with similar features?

In lessons learned from the Target case, what legal warnings would you give another retailer using data mining for marketing?

In data mining, finding an affinity of two products to be commonly together in a shopping cart is known as

When a problem has many attributes that impact the classification of different patterns, decision trees may be a useful approach.

Data that is collected, stored, and analyzed in data mining is often private and personal. There is no way to maintain individuals' privacy other than being very careful about physical data security.

Describe cluster analysis and some of its applications.

In the Memphis Police Department case study, predictive analytics helped to identify the best schedule for officers in order to pay the least overtime.

What are the differences between nominal, ordinal, interval and ratio data? Give examples.

In the opening vignette, Cabela's uses SAS data mining tools to create ________ models to optimize customer selection for all customer contacts.

List six common data mining mistakes.

What does the robustness of a data mining method refer to?

An Overview of Business Intelligence, Analytics, and Decision Support

Foundations and Technologies for Decision Making

Data Warehousing

Business Reporting, Visual Analytics, and Business Performance Management

Techniques for Predictive Modeling

Text Analytics, Text Mining, and Sentiment Analysis

Web Analytics, Web Mining, and Social Analytics

Model-Based Decision Making: Optimization and Multi-Criteria Systems

Modeling and Analysis: Heuristic Search Methods and Simulation

Automated Decision Systems and Expert Systems

Knowledge Management and Collaborative Systems

Big Data and Analytics

Business Analytics: Emerging Trends and Future Impacts

Filters

Exam 5: Data Mining

The number of users of free/open source data mining software now exceeds that of users of commercial software versions.

List five reasons for the growing popularity of data mining in the business world.

All of the following statements about data mining are true EXCEPT

The data field "ethnic group" can be best described as

The basic idea behind a ________ is that it recursively divides a training set until each division consists entirely or primarily of examples from one class.

While prediction is largely experience and opinion based, ________ is data and model based.

Prediction problems where the variables have numeric values are most accurately defined as

Understanding customers better has helped Amazon and others become more successful. The understanding comes primarily from

In the Cabela's case study, what types of models helped the company understand the value of customers, using a five-point scale?

Which broad area of data mining applications partitions a collection of objects into natural groupings with similar features?

In lessons learned from the Target case, what legal warnings would you give another retailer using data mining for marketing?

In data mining, finding an affinity of two products to be commonly together in a shopping cart is known as

When a problem has many attributes that impact the classification of different patterns, decision trees may be a useful approach.

Data that is collected, stored, and analyzed in data mining is often private and personal. There is no way to maintain individuals' privacy other than being very careful about physical data security.

Describe cluster analysis and some of its applications.

In the Memphis Police Department case study, predictive analytics helped to identify the best schedule for officers in order to pay the least overtime.

What are the differences between nominal, ordinal, interval and ratio data? Give examples.

In the opening vignette, Cabela's uses SAS data mining tools to create ________ models to optimize customer selection for all customer contacts.

List six common data mining mistakes.

What does the robustness of a data mining method refer to?

An Overview of Business Intelligence, Analytics, and Decision Support

Foundations and Technologies for Decision Making

Data Warehousing

Business Reporting, Visual Analytics, and Business Performance Management

Techniques for Predictive Modeling

Text Analytics, Text Mining, and Sentiment Analysis

Web Analytics, Web Mining, and Social Analytics

Model-Based Decision Making: Optimization and Multi-Criteria Systems

Modeling and Analysis: Heuristic Search Methods and Simulation

Automated Decision Systems and Expert Systems

Knowledge Management and Collaborative Systems

Big Data and Analytics

Business Analytics: Emerging Trends and Future Impacts

Filters