EXAM PA - QUALITATIVE SOA
QUESTIONS WITH CORRECT
ANSWERS
Describe the steps for developing a stratified sample. - Correct Answers -1. Identify the
strata
2. Draw a random sample from each stratum
3. Combine the samples above to create a stratified sample.
Discuss the advantages and disadvantages of using unstructured data in a predictive
model. - Correct Answers -Advantages:
- Unstructured data includes information that cannot be stored in a tabular format. Using
this unstructured data gives insights and qualitative information that cannot be included
in a structured dataset
Disadvantages:
- Unstructured data often requires more complex methods to process for input into a
predictive model. It can also be more time-consuming and resource-intensive to analyze
unstructured data
Describe two similarities and two differences between K-means clustering and
hierarchical clustering - Correct Answers -Similarities:
- K-means and hierarchical clustering can both be used to generate new features from
multiple predictor variables.
- K-means and hierarchical clustering are both unsupervised learning techniques, which
means that they both group observations to show structures and relationships in the
data without reference to a target variable.
Differences:
- K-means clustering requires choosing the number of clusters as an input. Hierarchical
clustering algorithms iteratively partition the data, resulting in models from one single
cluster to every observation being its own cluster. The results of the partitioning are
presented graphically in a dendrogram, where the modeler can then select K by making
a cut at a certain height.
- K-means only considers dissimilarity among observations (using, for example,
Euclidean distance) in creating clusters and does not have a notion of dissimilarity
among clusters. Hierarchical clustering algorithms do consider dissimilarity among
clusters through the use of a linkage function.
QUESTIONS WITH CORRECT
ANSWERS
Describe the steps for developing a stratified sample. - Correct Answers -1. Identify the
strata
2. Draw a random sample from each stratum
3. Combine the samples above to create a stratified sample.
Discuss the advantages and disadvantages of using unstructured data in a predictive
model. - Correct Answers -Advantages:
- Unstructured data includes information that cannot be stored in a tabular format. Using
this unstructured data gives insights and qualitative information that cannot be included
in a structured dataset
Disadvantages:
- Unstructured data often requires more complex methods to process for input into a
predictive model. It can also be more time-consuming and resource-intensive to analyze
unstructured data
Describe two similarities and two differences between K-means clustering and
hierarchical clustering - Correct Answers -Similarities:
- K-means and hierarchical clustering can both be used to generate new features from
multiple predictor variables.
- K-means and hierarchical clustering are both unsupervised learning techniques, which
means that they both group observations to show structures and relationships in the
data without reference to a target variable.
Differences:
- K-means clustering requires choosing the number of clusters as an input. Hierarchical
clustering algorithms iteratively partition the data, resulting in models from one single
cluster to every observation being its own cluster. The results of the partitioning are
presented graphically in a dendrogram, where the modeler can then select K by making
a cut at a certain height.
- K-means only considers dissimilarity among observations (using, for example,
Euclidean distance) in creating clusters and does not have a notion of dissimilarity
among clusters. Hierarchical clustering algorithms do consider dissimilarity among
clusters through the use of a linkage function.
