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PENGURUSAN DATA SAINS DAN ANALITIK

Total questions: 10

Worksheet time: 9mins

Name
Class
Date
1.

What is data science?

a)

The science of creating data.

b)

It is a branch of Social Studies.

c)

Multidisciplinary study of data collections for analysis, prediction, learning and prevention.

d)

It is a specialized field of study under Artificial Intelligence.

2.

Why do we need to prepare our data?

a)

Data might be invalid.

b)

Data might need to be transformed.

c)

Data might have outliers.

d)

All of the above

3.

Raw data should be processed only one time

a)

True

b)

False

4.

A brief step in Data Science is

a)

Data Modeling ->Data Acquisition -> Clean Data ->Data Analysis ->Deployment and optimization

b)

Data Acquisition -> Clean Data ->Data Analysis -> Data Modeling ->Deployment and optimization

c)

Clean Data ->Data Analysis -> Data Modeling ->Deployment and optimization -> Data Acquisition

d)

Data Modeling ->Data Acquisition -> Clean Data ->Data Analysis ->Deployment and optimization

5.

Which is not a tool for Graphical Data Analysis?

a)

Bar Chart

b)

Box Plot

c)

Linear Regression

d)

Scatter Plot

6.

All of the following statements are TRUE for machine learning algorithms except

a)

The classifier is domain dependent

b)

Difficult to get massive training data

c)

Has target data to calculate and minimize the error

d)

High computational time

7.

1. Suppose your task is to automate the assignment of new electronic products to your company’s product categories or catalogue, what would be the best approach to solve the problem

a)

Regression

b)

Clustering

c)

Classification

d)

Association rules

8.

In estimating the accuracy of classification models, the true positive rate is

a)

the ratio of correctly classified positives divided by the sum of correctly classified positives and incorrectly classified negatives.

b)

the ratio of correctly classified positives divided by the sum of correctly classified positives and incorrectly classified positives

c)

the ratio of correctly classified positives divided by the total positive count

d)

the ratio of correctly classified negatives divided by the total negative count

9.

The price of house property is measured in ringgit, bedrooms and the square fit. Suppose you want to use a machine learning algorithm to predict the price of the property for the next 5 years, how would you treat this problem

a)

Classification

b)

Clustering

c)

Regression

d)

Association rules

10.

Which of the following statement is TRUE?

a)

Representing data in a form which both mere mortals can understand and get valuable insights is as much a science as much as it is art

b)

None of the Mentioned

c)

Machine learning focuses on prediction, based on known properties learned from the training data

d)

Data Cleaning focuses on prediction, based on known properties learned from the training data.