QMB3302 FINAL EXAM {LATEST 2026 -
2027 update} QUESTIONS AND ANSWERS
100% CORRECT
If you are not careful or do not see the __________________ appropriately, leads to
decision trees overfitting - correct answer Max depth
The random forest algorithm prevents, or at least avoids to some extent, the problems
with overfitting found in decision trees. (True or False) - correct answer True
The correct number of clusters in Hierarchical clustering can be determined precisely
using approaches such as silhouette scores (True or False) - correct answer False
In K Means clustering, the analyst does not need to determine the number of clusters
(K), these are always derived analytically using the kmeans algorithm. (True or False)
- correct answer False
,One big difference between the unsupervised approaches in this module, and the
supervised approaches in prior modules: Unsupervised models do not have a target
variable (Y). This make is difficult to know when they are "right" or correct. (True or
False) - correct answer True
According to the documentation, a silhouette scores of 1 ia - correct answer The best
score
According to the documentation, a silhouette score of -1 is - correct answer The
worst score
Select all that apply. Imagine you have a data set with columns/inputs for customers:
Column 1 = Customer ID (a number)
, Column 2 = Sales (a dollar value)
Column 3= Frequency (a number)
Column 4 = Satisfaction (a number)
You would like to understand the impact of Frequency on customer Satisfaction. What
types of approaches could you use?
Note that the type of data is brackets () after the column name. - correct answer
Decision tree, random forest, linear regression
Select all that apply. Imagine you have a dataset with the following columns (inputs)
for a set of customers.
2027 update} QUESTIONS AND ANSWERS
100% CORRECT
If you are not careful or do not see the __________________ appropriately, leads to
decision trees overfitting - correct answer Max depth
The random forest algorithm prevents, or at least avoids to some extent, the problems
with overfitting found in decision trees. (True or False) - correct answer True
The correct number of clusters in Hierarchical clustering can be determined precisely
using approaches such as silhouette scores (True or False) - correct answer False
In K Means clustering, the analyst does not need to determine the number of clusters
(K), these are always derived analytically using the kmeans algorithm. (True or False)
- correct answer False
,One big difference between the unsupervised approaches in this module, and the
supervised approaches in prior modules: Unsupervised models do not have a target
variable (Y). This make is difficult to know when they are "right" or correct. (True or
False) - correct answer True
According to the documentation, a silhouette scores of 1 ia - correct answer The best
score
According to the documentation, a silhouette score of -1 is - correct answer The
worst score
Select all that apply. Imagine you have a data set with columns/inputs for customers:
Column 1 = Customer ID (a number)
, Column 2 = Sales (a dollar value)
Column 3= Frequency (a number)
Column 4 = Satisfaction (a number)
You would like to understand the impact of Frequency on customer Satisfaction. What
types of approaches could you use?
Note that the type of data is brackets () after the column name. - correct answer
Decision tree, random forest, linear regression
Select all that apply. Imagine you have a dataset with the following columns (inputs)
for a set of customers.
