Question 1

Single linkage can be used to measure the distance between clusters that are the __________ in cluster analysis.

Accepted Answer

A) most similar 
B) most different 
C) farthest apart 
D) closest 
A) most similar 
B) most different 
C) farthest apart 
D) closest

Question 2

The strength of a cluster can be measured by comparing the average distance in a cluster to the distance between cluster centroids. One rule of thumb is that the ratio for between-cluster distance to within-cluster distance should exceed what value for useful clusters?

Accepted Answer

A) 0.5 
B) 1 
C) 1.5 
D) 2 
A) 0.5 
B) 1 
C) 1.5 
D) 2

Question 3

Suppose that the confidence of an association rule is 0.75 and the total number of transactions is 250. How many of those transactions support the consequent if the lift ratio is 1.875?

Accepted Answer

A) 100 
B) 125 
C) 150 
D) 175 
A) 100 
B) 125 
C) 150 
D) 175

Question 4

A method for modifying variables that reduces bias prior to cluster analysis is

Accepted Answer

A) standardization. 
B) weighting. 
C) removing outliers. 
D) randomizing. 
A) standardization. 
B) weighting. 
C) removing outliers. 
D) randomizing.

Question 5

A collection of text documents to be analyzed is called a ___________.

Accepted Answer

A) book 
B) corpus 
C) library 
D) consequent 
A) book 
B) corpus 
C) library 
D) consequent

Question 6

In preparing categorical variables for analysis, it is usually best to

Accepted Answer

A) convert the categories to numeric representations. 
B) convert the categories to binary, dummy variables. 
C) combine as many categories as possible. 
D) let them remain categorical. 
A) convert the categories to numeric representations. 
B) convert the categories to binary, dummy variables. 
C) combine as many categories as possible. 
D) let them remain categorical.

Question 7

Which of the following is true of Euclidean distances?

Accepted Answer

A) It is used to measure dissimilarity between categorical variable observations. 
B) It is not affected by the scale on which variables are measured. 
C) It increases with the increase in similarity between variable values. 
D) It is commonly used as a method of measuring dissimilarity between quantitative observations. 
A) It is used to measure dissimilarity between categorical variable observations. 
B) It is not affected by the scale on which variables are measured. 
C) It increases with the increase in similarity between variable values. 
D) It is commonly used as a method of measuring dissimilarity between quantitative observations.

Question 8

The goal of __________ is to use the variable values to identify relationships between observations.

Accepted Answer

A) unsupervised learning 
B) data mining 
C) McQuitty's method 
D) Ward's method 
A) unsupervised learning 
B) data mining 
C) McQuitty's method 
D) Ward's method

Question 9

A tree diagram used to illustrate the sequence of nested clusters produced by hierarchical clustering is known as a

Accepted Answer

A) dendrogram. 
B) scatter chart. 
C) decile-wise lift chart. 
D) cumulative lift tree. 
A) dendrogram. 
B) scatter chart. 
C) decile-wise lift chart. 
D) cumulative lift tree.

Question 10

__________ is a measure of calculating dissimilarity between clusters by considering only the two most dissimilar observations in the two clusters.

Accepted Answer

A) Single linkage 
B) Complete linkage 
C) Average linkage 
D) Average group linkage 
A) Single linkage 
B) Complete linkage 
C) Average linkage 
D) Average group linkage

Question 11

If the Euclidean distance were to be represented in a right triangle, which of the following would be considered the distance between two observations of a cluster?

Accepted Answer

A) The short leg 
B) The long leg 
C) The hypotenuse 
D) Euclidean distance is not related to right triangles. 
A) The short leg 
B) The long leg 
C) The hypotenuse 
D) Euclidean distance is not related to right triangles.

Question 12

Euclidean distance can be used to measure the distance between __________ in cluster analysis.

Accepted Answer

A) objects 
B) clusters 
C) observations 
D) ward 
A) objects 
B) clusters 
C) observations 
D) ward

Question 13

Euclidean distance can be used to calculate the dissimilarity between two observations. Let u = (25, $350) correspond to a 25-year-old customer that spent $350 at Store A in the previous fiscal year. Let v = (53, $420) correspond to a 53-year-old customer that spent $4,100 at Store A in the previous fiscal year. Calculate the dissimilarity between these two observations using Euclidean distance.

Accepted Answer

A) 66.21 
B) 72.28 
C) 75.39 
D) 88.57 
A) 66.21 
B) 72.28 
C) 75.39 
D) 88.57

Question 14

A __________ refers to the number of times a collection of items occurs together in a transaction data set.

Accepted Answer

A) consequent 
B) validation count 
C) support count 
D) antecedent 
A) consequent 
B) validation count 
C) support count 
D) antecedent

Question 15

In the text mining process, the text is first preprocessed by deriving a smaller set of _________ from the larger set of words contained in a collection of documents.

Accepted Answer

A) tokens 
B) stems 
C) terms 
D) stack 
A) tokens 
B) stems 
C) terms 
D) stack

Question 16

The process of extracting useful information from text data is known as __________.

Accepted Answer

A) text mining 
B) tokenization 
C) stemming 
D) corpus 
A) text mining 
B) tokenization 
C) stemming 
D) corpus

Question 17

Single linkage is a measure of calculating dissimilarity between clusters by

Accepted Answer

A) considering only the two most dissimilar observations in the two clusters. 
B) computing the average dissimilarity between every pair of observations between the two clusters. 
C) considering only the two most similar observations in the two clusters. 
D) considering the distance between the cluster centroids. 
A) considering only the two most dissimilar observations in the two clusters. 
B) computing the average dissimilarity between every pair of observations between the two clusters. 
C) considering only the two most similar observations in the two clusters. 
D) considering the distance between the cluster centroids.

Question 18

k-means clustering is the process of

Accepted Answer

A) agglomerating observations into a series of nested groups based on a measure of similarity. 
B) organizing observations into distinct groups based on a measure of similarity. 
C) reducing the number of variables to consider in data-mining. 
D) estimating the value of a continuous outcome variable. 
A) agglomerating observations into a series of nested groups based on a measure of similarity. 
B) organizing observations into distinct groups based on a measure of similarity. 
C) reducing the number of variables to consider in data-mining. 
D) estimating the value of a continuous outcome variable.

Question 19

When clustering only by dummy variables that represent categorical variables, the simplest measure of similarity between two observations is called the

Accepted Answer

A) matching coefficient. 
B) Jaccard's coefficient. 
C) Euclidean distance. 
D) antecedent. 
A) matching coefficient. 
B) Jaccard's coefficient. 
C) Euclidean distance. 
D) antecedent.

Question 20

__________ can be used to partition observations in a manner to obtain clusters with the least amount of information loss due to the aggregation.

Accepted Answer

A) Single linkage 
B) Ward's method 
C) Average group linkage 
D) Dendrogram 
A) Single linkage 
B) Ward's method 
C) Average group linkage 
D) Dendrogram

Single linkage can be used to measure the distance between clusters that are the __________ in cluster analysis.

The strength of a cluster can be measured by comparing the average distance in a cluster to the distance between cluster centroids. One rule of thumb is that the ratio for between-cluster distance to within-cluster distance should exceed what value for useful clusters?

Suppose that the confidence of an association rule is 0.75 and the total number of transactions is 250. How many of those transactions support the consequent if the lift ratio is 1.875?

A method for modifying variables that reduces bias prior to cluster analysis is

A collection of text documents to be analyzed is called a ___________.

In preparing categorical variables for analysis, it is usually best to

Which of the following is true of Euclidean distances?

The goal of __________ is to use the variable values to identify relationships between observations.

A tree diagram used to illustrate the sequence of nested clusters produced by hierarchical clustering is known as a

__________ is a measure of calculating dissimilarity between clusters by considering only the two most dissimilar observations in the two clusters.

If the Euclidean distance were to be represented in a right triangle, which of the following would be considered the distance between two observations of a cluster?

Euclidean distance can be used to measure the distance between __________ in cluster analysis.

A __________ refers to the number of times a collection of items occurs together in a transaction data set.

In the text mining process, the text is first preprocessed by deriving a smaller set of _________ from the larger set of words contained in a collection of documents.

The process of extracting useful information from text data is known as __________.

Single linkage is a measure of calculating dissimilarity between clusters by

k-means clustering is the process of

When clustering only by dummy variables that represent categorical variables, the simplest measure of similarity between two observations is called the

__________ can be used to partition observations in a manner to obtain clusters with the least amount of information loss due to the aggregation.

Introduction

Descriptive Statistics

Data Visualization

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Linear Regression

Time Series Analysis and Forecasting

Predictive Data Mining

Spreadsheet Models

Monte Carlo Simulation

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Decision Analysis

Filters

Exam 4: Descriptive Data Mining

Single linkage can be used to measure the distance between clusters that are the __________ in cluster analysis.

The strength of a cluster can be measured by comparing the average distance in a cluster to the distance between cluster centroids. One rule of thumb is that the ratio for between-cluster distance to within-cluster distance should exceed what value for useful clusters?

Suppose that the confidence of an association rule is 0.75 and the total number of transactions is 250. How many of those transactions support the consequent if the lift ratio is 1.875?

A method for modifying variables that reduces bias prior to cluster analysis is

A collection of text documents to be analyzed is called a ___________.

In preparing categorical variables for analysis, it is usually best to

Which of the following is true of Euclidean distances?

The goal of __________ is to use the variable values to identify relationships between observations.

A tree diagram used to illustrate the sequence of nested clusters produced by hierarchical clustering is known as a

__________ is a measure of calculating dissimilarity between clusters by considering only the two most dissimilar observations in the two clusters.

If the Euclidean distance were to be represented in a right triangle, which of the following would be considered the distance between two observations of a cluster?

Euclidean distance can be used to measure the distance between __________ in cluster analysis.

A __________ refers to the number of times a collection of items occurs together in a transaction data set.

In the text mining process, the text is first preprocessed by deriving a smaller set of _________ from the larger set of words contained in a collection of documents.

The process of extracting useful information from text data is known as __________.

Single linkage is a measure of calculating dissimilarity between clusters by

k-means clustering is the process of

When clustering only by dummy variables that represent categorical variables, the simplest measure of similarity between two observations is called the

__________ can be used to partition observations in a manner to obtain clusters with the least amount of information loss due to the aggregation.

Introduction

Descriptive Statistics

Data Visualization

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Linear Regression

Time Series Analysis and Forecasting

Predictive Data Mining

Spreadsheet Models

Monte Carlo Simulation

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Decision Analysis

Filters