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In today’s digital world, data is generated every moment. Whether it is the marks
obtained by you or runs scored a batsman or weather forecast done or amount of
pollution increased in the last 10 years, the average height of students in a class, patients’
records kept by the hospital etc. everything is data. However, you need to refine and
analyse this data in order to get useful information out of it. In this chapter, you will
learn how to handle, organise, group and present data using pictographs, bar graphs,
double bar graphs, histograms in order to infer meaningful information.
5.1 Introduction
5.2 Organising Data
5.3 Grouping Data
5.4 Circle Graph or Pie Chart
5.5 Chance and Probability
Section 5.2 - In this section, you will learn how to organise raw so that it is easy to
comprehend. You’ll make use of tally numbers and tables in order to organise the data
into a more meaningful form. You’ll also learn what frequency is and how it is helpful in
data organisation.
Section 5.3 - After organising, you’ll study how to group data. This is because a
frequency table for each observation can be too lengthy and inconvenient to
understand. Therefore it is important to learn how to group data such as 0-10, 10-20
and so on to understand the overall picture better.
Section 5.4 - In this section, you will get in-depth knowledge about circle graphs, also
known as pie charts. You will learn how to represent and analyze data using pie charts.
Section 5.5 - In this section, you will learn what probability is and how it is useful in
our everyday lives. You will understand terms like chances, outcome, occurrence,
random experiment, probability of an event, and more.
In this chapter, you are provided with several examples along with their solutions for a
clear understanding of Data Handling. To know more about Class 8 Maths Chapter 5
Data Handling, you should explore the exercises below. You can also download the
Data Handling Class 8 NCERT Solutions PDF, solved by expert Maths trainers.
Published on 2020-02-13 10:01:04 by arunima. Last Modified on 2020-02-13 10:01:04
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