Chapter 4

In the Influence Health case, the company was able to evaluate over ________ million records in only two days

195

All of the following statements about data mining are true EXCEPT 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.

Which data mining process/methodology is thought to be the most comprehensive, according to kdnuggets.com rankings? A) SEMMA B) proprietary organizational methodologies C) KDD Process D) CRISP-DM

CRISP-DM

________ was proposed in the mid-1990s by a European consortium of companies to serve as a nonproprietary standard methodology for data mining.

CRISP-DM

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

D) its ability to overcome noisy data to make somewhat accurate predictions

Which of the following is a data mining myth? A) Data mining is a multistep process that requires deliberate, proactive design and use. B) Data mining requires a separate, dedicated database. C) The current state-of-the-art is ready to go for almost any business. D) Newer Web-based tools enable managers of all educational levels to do data mining.

Data mining requires a separate, dedicated database

Data mining can be very useful in detecting patterns such as credit card fraud, but is of little help in improving sales.

FALSE

Data mining requires specialized data analysts to ask ad hoc questions and obtain answers quickly from the system.

FALSE

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.

FALSE

In the Dell cases study, the largest issue was how to properly spend the online marketing budget

FALSE

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

FALSE

In the cancer research case study, data mining algorithms that predict cancer survivability with high predictive power are good replacements for medical professionals.

FALSE

K-fold cross-validation is also called sliding estimation.

FALSE

Market basket analysis is a useful and entertaining way to explain data mining to a technologically less savvy audience, but it has little business significance.

FALSE

Open-source data mining tools include applications such as IBM SPSS Modeler and Dell Statistica.

FALSE

Ratio data is a type of categorical data.

FALSE

Statistics and data mining both look for data sets that are as large as possible.

FALSE

The entire focus of the predictive analytics system in the Infinity P&C case was on detecting and handling fraudulent claims for the company's benefit.

FALSE

In the opening case, police detectives used data mining to identify possible new areas of inquiry.

FAlSE

Converting continuous valued numerical variables to ranges and categories is referred to as discretization.

TRUE

During classification in data mining, a false positive is an occurrence classified as true by the algorithm while being false in reality.

TRUE

If using a mining analogy, "knowledge mining" would be a more appropriate term than "data mining."

TRUE

In data mining, classification models help in prediction.

TRUE

The cost of data storage has plummeted recently, making data mining feasible for more firms.

TRUE

Using data mining on data about imports and exports can help to detect tax avoidance and money laundering.

TRUE

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

TRUE

) In the Target case study, why did Target send a teen maternity ads? A) Target's analytic model confused her with an older woman with a similar name. B) Target was sending ads to all women in a particular neighborhood. C) Target's analytic model suggested she was pregnant based on her buying habits. D) Target was using a special promotion that targeted all teens in her geographical area.

Target's analytic model suggested she was pregnant based on her buying habits.

All of the following statements about data mining are true EXCEPT: A) The term is relatively new. B) Its techniques have their roots in traditional statistical analysis and artificial intelligence. C) The ideas behind it are relatively new. D) Intense, global competition make its application more important.

The ideas behind it are relatively new.

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

analyzing the vast data amounts routinely collected

In data mining, finding an affinity of two products to be commonly together in a shopping cart is known as A) association rule mining. B) cluster analysis. C) decision trees. D) artificial neural networks.

association rule mining.

What is the main reason parallel processing is sometimes used for data mining? A) because the hardware exists in most organizations, and it is available to use B) because most of the algorithms used for data mining require it C) because of the massive data amounts and search efforts involved D) because any strategic application requires parallel processing

because of the massive data amounts and search efforts involved

Which broad area of data mining applications analyzes data, forming rules to distinguish between defined classes? A) associations B) visualization C) classification D) clustering

classification

Which broad area of data mining applications partitions a collection of objects into natural groupings with similar features? A) associations B) visualization C) classification D) clustering

clustering

In the Dell case study, engineers working closely with marketing, used lean software development strategies and numerous technologies to create a highly scalable, singular ________.

data mart

Knowledge extraction, pattern analysis, data archaeology, information harvesting, pattern searching, and data dredging are all alternative names for ________.

data mining

Data preparation, the third step in the CRISP-DM data mining process, is more commonly known as ________.

data preprocessing

Data are often buried deep within very large ________, which sometimes contain data from several years.

databases

In the terrorist funding case study, an observed price ________ may be related to income tax avoidance/evasion, money laundering, or terrorist financing.

deviation

A data mining study is specific to addressing a well-defined business task, and different business tasks require A) general organizational data. B) general industry data. C) general economic data. D) different sets of data.

different sets of data.

Patterns have been manually ________ from data by humans for centuries, but the increasing volume of data in modern times has created a need for more automatic approaches.

extracted

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

forecasting

In the Influence Health case study, what was the goal of the system? A) locating clinic patients B) understanding follow-up care C) decreasing operational costs D) increasing service use

increasing service use

Identifying and preventing incorrect claim payments and fraudulent activities falls under which type of data mining applications? A) insurance B) retailing and logistics C) customer relationship management D) computer hardware and software

insurance

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

its ability to construct a prediction model efficiently given a large amount of data

In ________, a classification method, the complete data set is randomly split into mutually exclusive subsets of approximately equal size and tested multiple times on each left-out subset, using the others as a training set.

k-fold cross-validation

Fayyad et al. (1996) defined ________ in databases as a process of using data mining methods to find useful information and patterns in the data

knowledge discovery

There has been an increase in data mining to deal with global competition and customers' more sophisticated ________ and wants.

needs

The data field "ethnic group" can be best described as A) nominal data. B) interval data. C) ordinal data. D) ratio data.

nominal data

Prediction problems where the variables have numeric values are most accurately defined as A) classifications. B) regressions. C) associations. D) computations.

regressions.

Customer ________ management extends traditional marketing by creating one-on-one relationships with customers.

relationship

The data mining in cancer research case study explains that data mining methods are capable of extracting patterns and ________ hidden deep in large and complex medical databases.

relationships

) Third party providers of publicly available data sets protect the anonymity of the individuals in the data set primarily by A) asking data users to use the data ethically. B) leaving in identifiers (e.g., name), but changing other variables. C) removing identifiers such as names and social security numbers. D) letting individuals in the data know their data is being accessed.

removing identifiers such as names and social security numbers.

Clustering partitions a collection of things into segments whose members share A) similar characteristics. B) dissimilar characteristics. C) similar collection methods. D) dissimilar collection methods

similar characteristics.

Whereas ________ starts with a well-defined proposition and hypothesis, data mining starts with a loosely defined discovery statement.

statistics

In estimating the accuracy of data mining (or other) classification models, the true positive rate is A) the ratio of correctly classified positives divided by the total positive count. B) the ratio of correctly classified negatives divided by the total negative count. C) the ratio of correctly classified positives divided by the sum of correctly classified positives and incorrectly classified positives. D) the ratio of correctly classified positives divided by the sum of correctly classified positives

the ratio of correctly classified positives divided by the total positive count.the ratio of correctly classified positives divided by the total positive count.