The following Topics and Sub-Topics are covered in this chapter and are available on MSVgo:

When you think of Mathematics you probably think of it only as a branch of science, It is in fact, also data which is considered as the foundation stone of Science. In fact, the marks you obtained, your weight, the score you get, everything is data. Comprehending the meaning of data, methods, and ways of representing it in the form of graphs is the core component of data handling.

Here are a few real-life examples of data handling –

**Voter polls****Marketing survey****Tally charts of data****Numbers of pens/pencils you have****Marks you got in your exams**

Organising Data

The data provided is mostly in unorganized or raw form. To arrive at a meaningful conclusion, you need to extract the information efficiently. Let us try to understand with the help of an example –

A group of students was asked for their favorite fruits. The responses were –

Apple, Orange, Mango, Apple, Litchi, Mango, Orange, Litchi, Mango

The process of arranging these data in a meaningful manner to draw proper inferences is called **organising data**. For example –

FruitsNumber of StudentsApple2Orange2Mango3Litchi2

Grouping Data

Often the data provided is large. In such circumstances, data is arranged in a group. For example – Marks obtained by group are as follows- 21, 10, 30, 22, 30, 5, 30, 12, 25, 15, 26

GroupStudents (Frequency)0-10110-20320-307

Such representation of data is referred to as **grouping data** and the frequency obtained is called a grouped frequency distribution.

**Pie Chart **underscores the relationship between the circle and its parts. The circle is divided into different chunks. The size of every segment is related to the data it represents. In other words, each sector is proportional to the other. It is referred to as a **Circle graph **because it represents data as a circle.

How many times does it happen that when you take your umbrella with you, it doesn’t rain, and on the off chance that you neglect to take it one day, it rains heavily and you get all wet? There are numerous circumstances that we face in life where we need to take decisions depending on the likelihood of an outcome.

Chance means the happening of any event in the absence of any cause. Probability is one of the cardinal branches of mathematics and an important topic in data. In short, probability means possibility. It is the likelihood of the event to occur.

Probability of an event = **Number of outcomes that make an event **

** Total number of outcomes of the experiment **

**1. What is data in data handling in maths?**

Data alludes to any snippet of information that gets utilized for performing different numerical tasks. Data is a plural form of the word datum, a solitary type of data. Models – Facts, numbers, words, estimations, and measurements are examples of data.

**2. What are the types of data handling?**

Data can be handled in various ways. You can use the following data types for data handling-

**Qualitative Data**– This data provides descriptive information about something.**Quantitative Data**– This data imparts numerical information about something.

**3. How do you introduce data handling?**

** **Follow the steps below to introduce data handling-

- Start with the basics of handling like meaning and types of data
- Gradually try to learn the concepts with the help of examples.
- Lastly, begin with some interactive exercises or inquisitive questions on data handling. Understand the meaning in simple words and move steadily towards complex topics related to data handling.

**4. What is the purpose of data handling?**

- The main purpose of data handling is to present the data that is easily understood and proves to be helpful to others.
- Data handling helps in maintaining the integrity of research data that involves confidentiality, preservation, and retention of data for various mathematical purposes.

**5. How is data represented in data handling?**

You can represent data in the following ways-

- Bar Graph
- Line Graphs
- Pictographs
- Histograms
- Stem and Leaf Plot
- Dot Plots
- Frequency Distribution
- Cumulative Tables and Graphs

**6. What are the two ways of handling data?**

The two ways of handling data are as follows-

**Electronic Method-**When information is obtained, stored, archived, and disposed using electronic systems like computers, CD and pen drive, etc.**Non-electronic Method-**This method involves using non-electronic means like paper, notebooks, journals, and files for obtaining, storing, and data handling.

For better understanding, you can view videos on the MSVgo app. You can also get to resolve your **Data Handling Class 8** questions to enhance your comprehension of the subject matter. **MSVgo** is an application whose main objective is to help you to understand the principles and concepts with examples using explanatory visuals or animation.

Data handling is a pivotal chapter for exams. Preparing well can assure good marks in exams. Data handling is helpful in deriving solutions to complex problems, including real-life complexities.

- Rational Numbers
- Linear Equations in One Variable
- Understanding Quadrilaterals
- Practical Geometry
- Squares and Square Roots
- Cubes and Cube Roots
- Comparing Quantities
- Algebraic Expressions and Identities
- Visualizing Solid Shapes
- Mensuration
- Exponents and Powers
- Direct and Inverse Proportions
- Factorization
- Introduction to Graphs
- Playing With Numbers