QMB3302 UF FALL Final Exam Version 1&2 (2 Latest Versions)
QMB3302 UF FALL FINAL EXAM VERSION 1&2 (2 LATEST
VERSIONS) NEWEST 2025/2026 WITH COMPLETE QUESTIONS
AND CORRECT ANSWERS |ALREADY GRADED A+||BRAND NEW
VERSION!
Version 1
What is Scikit-learn?
a. A machine learning package in Python that has built in machine learning
algorithms we can use on our dataset.
b. A machine learning model in Python that allows us to use various machine
learning models on our dataset.
c. An algorithm that sorts through a string, iterating one value at a time until it has
reached the end of the string, at which point it returns the string ascending
alphabetical order.
d. The ideal model to use when we are in a situation where we want to separate
our data into clusters. - ANSWER-a
Which of the following best describes the difference between a supervised and an
unsupervised learning task in machine learning?
a. A supervised learning task is faster and more efficient than an unsupervised
learning task.
b. A supervised learning task can handle both numerical and categorical data,
while an unsupervised learning task can only handle numerical data.
c. A supervised learning task requires labeled data, while an unsupervised task
does not.
1|Page
, QMB3302 UF FALL Final Exam Version 1&2 (2 Latest Versions)
d. A supervised learning task involves clustering data into groups, while an
unsupervised learning task involves predicting a target variable. - ANSWER-c
Which is true about linear regression models?
a. They are easy to interpret.
b. They are always the best model to choose.
c. They are the optimal choice of model in a situation where we have unlabeled
data.
d. We want them to completely explain our dataset. - ANSWER-a
Pipelines are useful (in analytics with Python sense) for the following reasons?
(Choose all that apply)
a. Pipelines make it very easy to change small things in your model, like which
variables to include.
b. Pipelines help organize the code you used to clean and treat your data.
c. Pipelines make it easy to repeat/replicate steps and run multiple models.
d. Pipelines automatically update to new versions of Python.
e. Pipelines are good for moving data into your programing environment. -
ANSWER-a, b, c
The basic idea of a regression is very simple. We have some X values (we called
these ________) and some Y values (this is the variable we are trying to _____.
We could have multiple Y values, but that is not something we have covered. -
ANSWER-features, predict
2|Page
, QMB3302 UF FALL Final Exam Version 1&2 (2 Latest Versions)
Y and y-hat are a little different. Y is our target vector, and y-hat is an output in our
model that is a(n)......
a. a combination of XY intercept coordinates.
b. estimate or predictions of y.
c. the actual value of y.
d. an axis on our 2 way graph. - ANSWER-b
When looking at the code in the videos, we sometimes used a variable to hold our
model.
What is the significance of the word "model" in the below code?
model = LinearRegression(fit_intercept=True)
a. The word 'model' instantiates the method and calls the interpreter. Without this
specific word, no model functions are available.
b. Model is a named variable and is just holding our linear regression model. It
could be renamed anything. The word itself is not important. It is just a container.
c. The word 'model' calls the fit method. If another word is used in this example,
Python will not understand that it is a model that can be run. - ANSWER-B
What is a good model fit value?
a. R-squared of .8
b. 99% accurate.
c. 95% accurate.
d. R-squared of p-value minus .05
3|Page
, QMB3302 UF FALL Final Exam Version 1&2 (2 Latest Versions)
e. R-squared of .4
f. R-squared of .95
g. Unknowable without knowing/understanding the context and the domain. -
ANSWER-g
Imagine X in the below is a missing value. If I were to run a median imputer on this
set of data what would the returned value be?
50, 60, 70, 80, 100, 60, 5000, X
a. 50
b. 70
c. 80
d. An error
e. 100 - ANSWER-b
The features of the model...
a. Keep the model validation process stable.
b. Are always functions of each other.
c. None of these answers are correct.
d. Are used as proxies for y-hat/y (that is yhat divided by y) - ANSWER-c
What is the first variable in a decision tree called (before any of the branches)?
a. Root
b. Origin
4|Page
QMB3302 UF FALL FINAL EXAM VERSION 1&2 (2 LATEST
VERSIONS) NEWEST 2025/2026 WITH COMPLETE QUESTIONS
AND CORRECT ANSWERS |ALREADY GRADED A+||BRAND NEW
VERSION!
Version 1
What is Scikit-learn?
a. A machine learning package in Python that has built in machine learning
algorithms we can use on our dataset.
b. A machine learning model in Python that allows us to use various machine
learning models on our dataset.
c. An algorithm that sorts through a string, iterating one value at a time until it has
reached the end of the string, at which point it returns the string ascending
alphabetical order.
d. The ideal model to use when we are in a situation where we want to separate
our data into clusters. - ANSWER-a
Which of the following best describes the difference between a supervised and an
unsupervised learning task in machine learning?
a. A supervised learning task is faster and more efficient than an unsupervised
learning task.
b. A supervised learning task can handle both numerical and categorical data,
while an unsupervised learning task can only handle numerical data.
c. A supervised learning task requires labeled data, while an unsupervised task
does not.
1|Page
, QMB3302 UF FALL Final Exam Version 1&2 (2 Latest Versions)
d. A supervised learning task involves clustering data into groups, while an
unsupervised learning task involves predicting a target variable. - ANSWER-c
Which is true about linear regression models?
a. They are easy to interpret.
b. They are always the best model to choose.
c. They are the optimal choice of model in a situation where we have unlabeled
data.
d. We want them to completely explain our dataset. - ANSWER-a
Pipelines are useful (in analytics with Python sense) for the following reasons?
(Choose all that apply)
a. Pipelines make it very easy to change small things in your model, like which
variables to include.
b. Pipelines help organize the code you used to clean and treat your data.
c. Pipelines make it easy to repeat/replicate steps and run multiple models.
d. Pipelines automatically update to new versions of Python.
e. Pipelines are good for moving data into your programing environment. -
ANSWER-a, b, c
The basic idea of a regression is very simple. We have some X values (we called
these ________) and some Y values (this is the variable we are trying to _____.
We could have multiple Y values, but that is not something we have covered. -
ANSWER-features, predict
2|Page
, QMB3302 UF FALL Final Exam Version 1&2 (2 Latest Versions)
Y and y-hat are a little different. Y is our target vector, and y-hat is an output in our
model that is a(n)......
a. a combination of XY intercept coordinates.
b. estimate or predictions of y.
c. the actual value of y.
d. an axis on our 2 way graph. - ANSWER-b
When looking at the code in the videos, we sometimes used a variable to hold our
model.
What is the significance of the word "model" in the below code?
model = LinearRegression(fit_intercept=True)
a. The word 'model' instantiates the method and calls the interpreter. Without this
specific word, no model functions are available.
b. Model is a named variable and is just holding our linear regression model. It
could be renamed anything. The word itself is not important. It is just a container.
c. The word 'model' calls the fit method. If another word is used in this example,
Python will not understand that it is a model that can be run. - ANSWER-B
What is a good model fit value?
a. R-squared of .8
b. 99% accurate.
c. 95% accurate.
d. R-squared of p-value minus .05
3|Page
, QMB3302 UF FALL Final Exam Version 1&2 (2 Latest Versions)
e. R-squared of .4
f. R-squared of .95
g. Unknowable without knowing/understanding the context and the domain. -
ANSWER-g
Imagine X in the below is a missing value. If I were to run a median imputer on this
set of data what would the returned value be?
50, 60, 70, 80, 100, 60, 5000, X
a. 50
b. 70
c. 80
d. An error
e. 100 - ANSWER-b
The features of the model...
a. Keep the model validation process stable.
b. Are always functions of each other.
c. None of these answers are correct.
d. Are used as proxies for y-hat/y (that is yhat divided by y) - ANSWER-c
What is the first variable in a decision tree called (before any of the branches)?
a. Root
b. Origin
4|Page
