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STSCI 3740: Lecture 1

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

What is the primary goal of supervised learning?

a)

To predict or estimate an output based on input data

b)

To visualize data in a 2D space

c)

To reduce the number of features

d)

To find groups of samples that behave similarly

2.

Which method is used to predict categorical or qualitative outcomes?

a)

Linear regression

b)

Principal Component Analysis

c)

Classification

d)

Clustering

3.

Which of the following is an example of an unsupervised learning problem?

a)

Predicting wages based on age and education

b)

Predicting whether the S&P 500 index will increase or decrease

c)

Grouping customers based on demographic data

d)

Predicting future stock prices

4.

What is the goal of Principal Component Analysis (PCA) in the context of gene expression data?

a)

To reduce the number of gene expression for visualization

b)

To perform linear regression

c)

To predict future gene expressions

d)

To classify cancer types

5.

Which of the following statements is true about linear regression?

a)

It is a non-linear method

b)

It is used for predicting qualitative values

c)

It is used for predicting quantitative values

d)

It was developed in the early 1970s

6.

What is the main difference between regression and classification problems?

a)

Regression uses PCA, while classification uses clustering

b)

Regression is a type of unsupervised learning, while classification is supervised

c)

Regression predicts continuous outputs, while classification predicts categorical outcomes

d)

Regression is used for gene expression data, while classification is used for stock market data

7.

Which of the following is a key aspect of statistical learning?

a)

It includes both supervised and unsupervised learning methods

b)

It is not useful in finance

c)

It only involves linear methods

d)

The more complicated is a method the better it performs

8.

What is the purpose of model selection in supervised learning?

a)

To reduce the number of features

b)

To group similar samples

c)

To visualize data in a 2D space

d)

To find the best model for the outcome or which inputs affect the outcome

9.

Which of the following is an example of a regression problem ?

a)

Grouping customers based on purchasing behaviour

b)

Classifying emails as spam or not

c)

Predicting wages based on age and education

d)

Predicting whether a stock will up or down

10.

What is the main goal of unsupervised learning ?

a)

Find groups or clusters within the data

b)

Select the best model for prediction

c)

Predict future outcomes

d)

Estimate the effect of inputs on outcomes