# NCERT Solutions for Class 6 Maths Chapter 9 Exercise 9.1

NCERT Solutions for Class 6 Maths Chapter 9 Exercise 9.1 (Ex. 9.1) Data Handling updated for academic session 2020-2021 free to download or study online. All the questions are solved step by step in PDF as well as in explanation videos.

Class 6 Maths exercises 9.1 all the questions are explained in simple format using explanation videos. In PDF solutions also our subject experts have used simple steps to solve the questions.## Class 6 Maths Chapter 9 Exercise 9.1 Solution

Class: 6 | Mathematics |

Chapter: 9 | Data Handling |

Exercise: 9.1 | PDF and Videos Solution |

### CBSE NCERT Class 6 Maths Chapter 9 Exercise 9.1 Solution in Hindi and English Medium

### Class 6 Maths Chapter 9 Exercise 9.1 Solution in Videos

#### Data

A data means information in the form of numerical figures.

Example:

The weights (in kg) of 10 students of a class are:

42, 36, 34, 45, 48, 52, 39, 40, 43, 47,

We call it the data related to the weights of 10 students of a class.

##### Raw Data

Data obtained in the original form is called raw data. Data given in the above examples are raw data.

##### Observations

Each numerical figure in a data is called an observation.

##### Array

Arranging the numerical figures in an ascending or a descending order is called an array.

##### Tabulation of Data

Arranging the data in a systematic form in the form of a table is called tabulation or presentation of the data.

##### Frequency of an observation

The number of times a particular observation occurs is called its frequency.

Example:

Following are the number of members in 20 families in a village.

6, 8, 6, 3, 2, 5, 7, 8, 6, 5, 7, 5, 7, 6, 8, 7, 6, 6, 7, 5

Arrange the above data in an ascending order and then put it in the tabular form.

Ans: Arranging the data in an ascending order, we get the given data as

2, 3, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8

##### What are the types of data handling?

Types of Data Handling:

Bar Graph.

Pictograph.

Line Graph.

Stem and Leaf Plots.

Histogram.

Dot Plots.

Cumulative Tables and graphs.

Frequency Distribution.

##### What is the importance of data handling?

Data handling is important in ensuring the integrity of research data since it addresses concerns related to confidentially, security, and preservation/retention of research data. Proper planning for data handling can also result in efficient and economical storage, retrieval, and disposal of data.

##### How does data handling relate to real life?

When you relate observations to your school data or real-life examples, you can understand its usage practically. Lat’s study some practical examples of data handling. The number of pastries remaining after your school baking sale.

(i) Voter Polls

(ii) Marketing Surveys

(iii) The temperature of different cities in your country.