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DATA ANALYTICS

Total questions: 25

Worksheet time: 50mins

Name
Class
Date
1.

Which statement best describes the trend in the data?

a)

As temperatures increase, ice cream cone sales decrease.

b)

As temperatures increase, ice cream cone sales increase.

c)

There is no trend in the data.

d)

As temperatures decrease, ice cream cone sales increase.

2.

The highest number minus the lowest number in a set of data is called the __________

a)

mean

b)

median

c)

range

d)

maximum

3.

Data Analytics uses __________ to get insights from data.

a)

Statistical figures

b)

Statistical methods

c)

Numerical aspects

d)

None of the mentioned above

4.

Linear Regression is the supervised machine learning model in which the model finds the best fit _____ between the independent and dependent variable.

a)

Linear line

b)

Nonlinear line

c)

Curved line

d)

All of the mentioned above

5.

Amongst which of the following is / are the types of Linear Regression,

a)

Simple Linear Regression

b)

Multiple Linear Regression

c)

Both A and B

d)

None of the mentioned above

6.

Error is the difference between the actual value and Predicted value and the goal is to reduce this difference.

a)

True

b)

False

7.

A graph that uses vertical bars to represent data is called a ____.

a)

Line graph

b)

Bar graph

c)

Scatterplot

d)

All of the mentioned above

8.

Data Analysis is a process of,

a)

Inspecting data

b)

Data Cleaning

c)

Transforming of data

d)

All of the mentioned above

9.

For each value of the _____, the distribution of the dependent variable must be normal.

a)

Independent variable

b)

Depended variable

c)

Intermediate variable

d)

None of the mentioned above

10.

Amongst which of the following is / are not a major data analysis approach?

a)

Business Intelligence

b)

Data Mining

c)

Text Analytics

d)

Predictive Intelligence

11.

If the null hypothesis is false then which of the following is accepted?

a)

Alternative Hypothesis.

b)

Null Hypothesis

c)

Both A and B

d)

None of the mentioned above

12.

_______ refers to the ability to turn your data useful for business.

a)

Value

b)

Variety

c)

Velocity

d)

None of the mentioned above

13.

A good data analytics solution includes a viable self-service ___.

a)

Data mining

b)

Data wrangling

c)

Data warehouse

d)

None of the mentioned above

14.

To glean insights from the data, many analysts and data scientists rely on ___.

a)

Data mining

b)

Data warehouse

c)

Data visualization

d)

All of the mentioned above

15.

Predictive analytics involves taking historical data ---

a)

True

b)

False

16.

______ are the basic building blocks of qualitative data.

a)

Categories

b)

Data chunk

c)

Numeric figures

d)

None of the mentioned above

17.

Tableau is a ________ tool.

a)

Analytical

b)

Visualization

c)

Data Exploration

d)

All of the mentioned above

18.

Text Analytics, also referred to as Text Mining?

a)

True

b)

False

c)

Can be True or False

d)

Can not say

19.

_____ is a method in which data is collected and organized so that one can look at what the data is trying to tell us.

a)

Data collection

b)

Data analysis

c)

Data organization

d)

Data function

20.

Which of the following is not one of the four V’s of Big Data?

a)

Velocity

b)

Volume

c)

Variety

d)

Value

21.

What is the process of transforming structured and unstructured data into a format that can be easily analyzed?

a)

Data Mining

b)

Data Warehousing

c)

Data Integration

d)

Data Processing

22.

Which of the following is a tool used for processing and analyzing Big Data?

a)

Hadoop

b)

PostgreSQL

c)

MySQL

d)

Oracle

23.

What is the process of storing and managing data in a way that allows for efficient retrieval and analysis?

a)

Data Mining

b)

Data Processing

c)

Data Warehousing

d)

Data Integration

24.

What is the process of combining data from multiple sources into a single, unified view?

a)

Data Mining

b)

Data Warehousing

c)

Data Processing

d)

Data Integration

25.

What is the process of cleaning and transforming data before it is used for analysis?

a)

Data Mining

b)

Data Preprocessing

c)

Data Integration

d)

Data Warehousing