STSCI 3740: Lecture 1
Quiz
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Others
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University
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Medium
Nayel Bettache
Used 1+ times
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary goal of supervised learning?
To predict or estimate an output based on input data
To visualize data in a 2D space
To reduce the number of features
To find groups of samples that behave similarly
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which method is used to predict categorical or qualitative outcomes?
Linear regression
Principal Component Analysis
Classification
Clustering
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is an example of an unsupervised learning problem?
Predicting wages based on age and education
Predicting whether the S&P 500 index will increase or decrease
Grouping customers based on demographic data
Predicting future stock prices
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the goal of Principal Component Analysis (PCA) in the context of gene expression data?
To reduce the number of gene expression for visualization
To perform linear regression
To predict future gene expressions
To classify cancer types
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following statements is true about linear regression?
It is a non-linear method
It is used for predicting qualitative values
It is used for predicting quantitative values
It was developed in the early 1970s
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main difference between regression and classification problems?
Regression uses PCA, while classification uses clustering
Regression is a type of unsupervised learning, while classification is supervised
Regression predicts continuous outputs, while classification predicts categorical outcomes
Regression is used for gene expression data, while classification is used for stock market data
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is a key aspect of statistical learning?
It includes both supervised and unsupervised learning methods
It is not useful in finance
It only involves linear methods
The more complicated is a method the better it performs
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