AN 300 -EXAM 2 QUESTIONS ANSWERED CORRECTLY LATEST UPDATE 2026
Which of the following is true about cluster analysis? Check all that apply.
-It is a descriptive analytics technique
-It is to discover associations between objects.
-It is used to discover natural groupings of objects.
-It is to answer what has happened questions.
-It is a descriptive analytics method.
-It is to answer what could happen questions. - Answers -It is a descriptive analytics technique.
-It is used to discover natural groupings of objects.
-It is to answer what has happened questions.
Which of the following is a characteristic of a cluster analysis problem? (Check all that apply):
-The data that describes the object must be given.
-Its objective is to maximize similarities of objects between groups.
-The data on group memberships must be given.
-It is about how to discover
-It is about how to organize objects into groups.
-Its objective is to maximize similarities of objects within groups. - Answers -The data that describes
the object must be given.
-It is about how to organize objects into groups.
-Its objective is to maximize similarities of objects within groups.
You have data on the weight and height of patients. Which similarity measure should be used to
calculate how similar a group of patients is to one another?
-Manhattan coefficient
-Correlation coefficient
-Euclidean distance
-Matching coefficient
-Straight line distance - Answers -Euclidean distance
You have data on the gender and income levels of customers. Which similarity measure should be
used to calculate how similar a group of customers is to one another?
-Correlation coefficient
-Matching coefficient
-Straight line distance
-Manhattan coefficient
-Euclidean distance - Answers -Matching coefficient
Match the description on the left with the measure to use on the right.
-It is the length of a straight line between two objects. - Answers Euclidian Distance
It requires replacing the raw value of data with its z-score. - Answers Euclidian Distance
The lower the measure the better - Answers Euclidian Distance
It is for categorical Data - Answers Matching Coefficient
It is a ratio of number of columns with matching categorical values to the total number of categorical
columns. - Answers Matching Coefficient
Which of the following is a business application of cluster analysis?
-Affinity analysis
-Outlier detection
-Market basket analysis
-Sentiment analysis - Answers -Outlier detection
Match the situation on the left with the clustering method on the right.
-You have 300 rows of data. - Answers Hierarchical Clustering
You only have numerical data to work with. - Answers K-Means Clustering
You have outliers in the data. - Answers K-Means Clustering
You want to experiment with different ways to calculate the distance between clusters. - Answers
Hierarchical Clustering
Which of the following is true about CCC? Check all that apply.
-A value greater than two is highly desirable.
-It is used to tell the goodness of fit of clustering.
, -It stands for Cubic Clustering Criterion.
-It is related to the proportion of variance in the data accounted for by the clusters.
-It is related to the proportion of matching values in a column against all columns.
-A negative value is impossible.
-It stands for Complete Clustering Criterion. - Answers -A value greater than two is highly desirable.
-It is used to tell the goodness of fit of clustering.
-It stands for Cubic Clustering Criterion.
-It is related to the proportion of variance in the data accounted for by the clusters.
Which of the following is TRUE about the Hierarchical Clustering process? Check all that apply.
-Each object is assigned to one of the k clusters based on a seed point.
-Clusters are stabilized when stopped.
-Each object is placed in its own cluster when started.
-All objects are placed in one cluster when stopped.
-Reassigns each object to a cluster based on the cluster means in each iteration.
-Single linkage is the default distance measure used in JMP Pro
-Ward's minimum variance is the default distance measure used in JMP Pro.
-Two most similar clusters are combined into one in each iteration. - Answers -Each object is placed
in its own cluster when started.
-All objects are placed in one cluster when stopped.
-Ward's minimum variance is the default distance measure used in JMP Pro.
-Two most similar clusters are combined into one in each iteration.
Which of the following is TRUE about the K-Means Clustering process? Check all that apply.
-All objects are placed in one cluster when stopped.
-Reassigns each object to a cluster based on the cluster means in each iteration.
-Ward's minimum variance is the default distance measure used in JMP Pro.
-Each object is assigned to one of the k clusters based on a seed point.
-Each object is placed in its own cluster when started.
-Clusters are stabilized when stopped.
-Two most similar clusters are combined into one in each iteration.
-A specific number of clusters must be given to start the process. - Answers -Reassigns each object to
a cluster based on the cluster means in each iteration.
-Each object is assigned to one of the k clusters based on a seed point.
-Clusters are stabilized when stopped.
-A specific number of clusters must be given to start the process.
Match the visual on the left with the cluster analysis method on the right.
-Dendrogram - Answers Hierarchical Clustering
Constellation Plot - Answers Hierarchical Clustering
Biplot - Answers K-means Clustering
Parallel coordinates plot - Answers K-means Clustering
Which of the following is TRUE about association rule analysis? Check all that apply.
-It is a descriptive analytics method.
-It answers the what has happened questions.
-It is used to discover natural connections among objects.
-It is called affinity analysis.
-It is used to discover nontrivial what goes with what connections among groups of items in distinct
events.
-It answers the what should happen questions. - Answers -It answers the what has happened
questions.
-It is called affinity analysis.
-It is used to discover nontrivial what goes with what connections among groups of items in distinct
events.
What kind of problems are appropriate for association rule analysis? Check all that apply.
-The problem solution is expressed as a set of IF-THEN statements expressing the likelihood of co-
occurrence of objects.
-The problem has data that describes the co-occurrences of objects in distinct events.
-The problem solution is expressed as groupings of objects that have a high likelihood of co-
occurrences.
Which of the following is true about cluster analysis? Check all that apply.
-It is a descriptive analytics technique
-It is to discover associations between objects.
-It is used to discover natural groupings of objects.
-It is to answer what has happened questions.
-It is a descriptive analytics method.
-It is to answer what could happen questions. - Answers -It is a descriptive analytics technique.
-It is used to discover natural groupings of objects.
-It is to answer what has happened questions.
Which of the following is a characteristic of a cluster analysis problem? (Check all that apply):
-The data that describes the object must be given.
-Its objective is to maximize similarities of objects between groups.
-The data on group memberships must be given.
-It is about how to discover
-It is about how to organize objects into groups.
-Its objective is to maximize similarities of objects within groups. - Answers -The data that describes
the object must be given.
-It is about how to organize objects into groups.
-Its objective is to maximize similarities of objects within groups.
You have data on the weight and height of patients. Which similarity measure should be used to
calculate how similar a group of patients is to one another?
-Manhattan coefficient
-Correlation coefficient
-Euclidean distance
-Matching coefficient
-Straight line distance - Answers -Euclidean distance
You have data on the gender and income levels of customers. Which similarity measure should be
used to calculate how similar a group of customers is to one another?
-Correlation coefficient
-Matching coefficient
-Straight line distance
-Manhattan coefficient
-Euclidean distance - Answers -Matching coefficient
Match the description on the left with the measure to use on the right.
-It is the length of a straight line between two objects. - Answers Euclidian Distance
It requires replacing the raw value of data with its z-score. - Answers Euclidian Distance
The lower the measure the better - Answers Euclidian Distance
It is for categorical Data - Answers Matching Coefficient
It is a ratio of number of columns with matching categorical values to the total number of categorical
columns. - Answers Matching Coefficient
Which of the following is a business application of cluster analysis?
-Affinity analysis
-Outlier detection
-Market basket analysis
-Sentiment analysis - Answers -Outlier detection
Match the situation on the left with the clustering method on the right.
-You have 300 rows of data. - Answers Hierarchical Clustering
You only have numerical data to work with. - Answers K-Means Clustering
You have outliers in the data. - Answers K-Means Clustering
You want to experiment with different ways to calculate the distance between clusters. - Answers
Hierarchical Clustering
Which of the following is true about CCC? Check all that apply.
-A value greater than two is highly desirable.
-It is used to tell the goodness of fit of clustering.
, -It stands for Cubic Clustering Criterion.
-It is related to the proportion of variance in the data accounted for by the clusters.
-It is related to the proportion of matching values in a column against all columns.
-A negative value is impossible.
-It stands for Complete Clustering Criterion. - Answers -A value greater than two is highly desirable.
-It is used to tell the goodness of fit of clustering.
-It stands for Cubic Clustering Criterion.
-It is related to the proportion of variance in the data accounted for by the clusters.
Which of the following is TRUE about the Hierarchical Clustering process? Check all that apply.
-Each object is assigned to one of the k clusters based on a seed point.
-Clusters are stabilized when stopped.
-Each object is placed in its own cluster when started.
-All objects are placed in one cluster when stopped.
-Reassigns each object to a cluster based on the cluster means in each iteration.
-Single linkage is the default distance measure used in JMP Pro
-Ward's minimum variance is the default distance measure used in JMP Pro.
-Two most similar clusters are combined into one in each iteration. - Answers -Each object is placed
in its own cluster when started.
-All objects are placed in one cluster when stopped.
-Ward's minimum variance is the default distance measure used in JMP Pro.
-Two most similar clusters are combined into one in each iteration.
Which of the following is TRUE about the K-Means Clustering process? Check all that apply.
-All objects are placed in one cluster when stopped.
-Reassigns each object to a cluster based on the cluster means in each iteration.
-Ward's minimum variance is the default distance measure used in JMP Pro.
-Each object is assigned to one of the k clusters based on a seed point.
-Each object is placed in its own cluster when started.
-Clusters are stabilized when stopped.
-Two most similar clusters are combined into one in each iteration.
-A specific number of clusters must be given to start the process. - Answers -Reassigns each object to
a cluster based on the cluster means in each iteration.
-Each object is assigned to one of the k clusters based on a seed point.
-Clusters are stabilized when stopped.
-A specific number of clusters must be given to start the process.
Match the visual on the left with the cluster analysis method on the right.
-Dendrogram - Answers Hierarchical Clustering
Constellation Plot - Answers Hierarchical Clustering
Biplot - Answers K-means Clustering
Parallel coordinates plot - Answers K-means Clustering
Which of the following is TRUE about association rule analysis? Check all that apply.
-It is a descriptive analytics method.
-It answers the what has happened questions.
-It is used to discover natural connections among objects.
-It is called affinity analysis.
-It is used to discover nontrivial what goes with what connections among groups of items in distinct
events.
-It answers the what should happen questions. - Answers -It answers the what has happened
questions.
-It is called affinity analysis.
-It is used to discover nontrivial what goes with what connections among groups of items in distinct
events.
What kind of problems are appropriate for association rule analysis? Check all that apply.
-The problem solution is expressed as a set of IF-THEN statements expressing the likelihood of co-
occurrence of objects.
-The problem has data that describes the co-occurrences of objects in distinct events.
-The problem solution is expressed as groupings of objects that have a high likelihood of co-
occurrences.
