Data handling is a statistic that we can consider as a useful concept to ensure the research data integrity. The concept addresses the security, preservation, and confidentiality of the research data. Data handling in maths mostly includes numeric data in each field. Numerical figures are essential to figure out data and statistics. All the numeric values are called observations. Well, you will get to know all the details like what is data handling, and examples will help you to discover how to represent data. Mainly, all the observations are known as data collectively. However, many data management tactics are known, and statisticians use them to handle the data. Let’s look into the data and statistics and methods.
Well, you probably know the term data but data, i.e. observations seem to be useful when you represent accurately. Numeric figures are collectively known as data, and specific data represent specific information. Well, here we can consider anything as data that means data may include measurements, descriptions, numbers, words, observations. Data management is the process of securing researched data for the analysis process and even after completion of any analysis process.
Types Of Data: Data Handling In Maths
Well, to perform any data handling method, you must know the types of data. Data or observations are classified into mainly two types.
Qualitative Data
Quantitative Data
Qualitative data is descriptive information, and quantitative data is numerical information. Furthermore, we can divide quantitative data into two sections, like continuous data and discrete data. Data that contain some specific values like whole numbers are separate data. Whereas continuous data can include any value from the given range.
Data Handling Examples
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.
Make a tally chart of colours of bags all students carry to the school.
Draw a chart of the number of girls and boys in your class or school.
Create a circular chart of colours liked by your family members.
Make a tally chart of absent students per each class.
Examples: Related To Real Life
Voter Polls
Marketing Surveys
The temperature of different cities in your country.
Types Of Data Handling:
Data can be observed from many factors like you can take the running time of different people, marks obtained by different students, daily calorie consumption, etc. All such observation is data and representation of data by different types of data handling will help you to get the critical values for experiments. You can organize data in various types like in the chart or graph.
How to Represent Data?
You can use any method to represent your collected data according to your required results.
Bar Graph
Pictographs
Line Graphs
Stem and Leaf Plot
Histograms
Dot Plots
Cumulative Tables and Graphs
Frequency Distribution
The bar graph is a very common, useful and straightforward method to represent the data. Let’s study Bar Graph with example.
Representation Of Data: Bar Graph
Numbers, pictures, graphics, and tables can be used to represent the data, and the most common method is a bar graph. In the bar graph method, all data is represented as bars, and it will give the bright idea of increment or decrement of any entity. The bar graph is also considered as a bar chart. There is a plane of vertical and horizontal lines to present the data as bars. Bars are rectangular flat visuals that place according to the researched observations. Bar length is proportional to the given entities. Well, the following example will help you to understand the bar graph.
Solved Examples: Bar Graph
Marks and attendance of about 400 students from the school are collected in a table. Represent the data with the bar graph method.
Table Of Data to Make The Bar Graph
Bar Graph
Each bar in the above example is of uniform width, and the data which varies is represented on one of the axes. Another axis represents the measure of the variable data through the height of the bars. The heights or the lengths of the bars denote the value of the variable. These graphs are also used to compare specific quantities.
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X-axes represent the attendance of all students, and Y-axes represent the number of students. The length of bars represents the number of students, and all the bars are the same in width. Well, after drafting bars in the chart, we can conclude the attendance of students in the school. We can find the following points by observing the above graph.
Number of students with 60% attendance: 105
Number of students with 70% attendance: 199
Number of students with 80% attendance: 29
Number of students with 90% attendance: 73
So, the bar graph will make your analysis organized and straightforward.
Solved Example:
The pie chart of 120 students representing their favourite juice is given below. From the chart, provide the answer to the simple questions given below.
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1.Is the Pie Chart More Useful Than a Bar Chart?
The pie chart is the best way to visualize data in percentage, and you can check the relative proportion of the given data.
2. What Data Cannot be Obtained from the Above Pie Chart?
The number of students who like the same juice.
3. Which Juice Do Students Love The Most?
Fruit cocktail.
4. Which Juice Is Wanted By The Same Number of Total Students?
Grape juice and apple juice.
FAQs on Data Handling
1. What is data handling, and why is it important in Class 8 Maths?
Data handling means collecting, organizing, and representing information so it can be easily understood and analyzed. In Class 8 Maths, learning data handling helps students interpret real-life information, draw logical conclusions, and make decisions using charts and graphs, as per the CBSE 2025-26 syllabus.
2. How do you differentiate between a bar graph and a pie chart in terms of their application for data handling?
A bar graph is ideal for comparing quantities of different categories, as it shows data as bars of varying heights. A pie chart is most effective for visualizing data as parts of a whole, especially when displaying percentages or proportions. Choosing the correct representation enhances clarity in data handling tasks.
3. What are the sequential steps followed in processing data for any mathematical investigation?
To handle data systematically in Maths, follow these steps:
- Define the purpose of data collection
- Identify required data fields
- Choose a data collection method
- Collect the data
- Organize and analyze the data
4. Why is it necessary to organize raw data into tables before making graphs?
Organizing raw data into tables helps in identifying patterns, spotting inconsistencies, and simplifying information. It provides a foundation for accurate bar graphs or pie charts, ensuring graphical representations in Maths are precise and meaningful.
5. What common mistakes do students make while drawing a bar graph, and how can they be avoided?
Students often make errors such as unequal bar widths, inconsistent spacing, or mislabeling axes. To avoid these, ensure:
- All bars are of equal width
- Axes are clearly labeled with data categories and values
- Use a uniform scale
- Bars are spaced evenly
6. How does representing data graphically benefit decision making in real-life scenarios?
Graphical representation makes complex data easy to interpret, highlights trends and differences, and supports quick decision making. For example, schools use bar graphs to track attendance or pie charts to understand students’ preferences, making data handling vital beyond the classroom.
7. What types of questions can be answered using information from a bar graph and what cannot?
A bar graph can answer questions like 'Which category has the highest/lowest value?', 'What is the difference between two categories?', and 'How many items belong to each group?'. It cannot show how parts relate to a whole or represent data in percentages—that’s where a pie chart is more useful.
8. In what situations is a pie chart less effective than a bar graph for presenting data?
Pie charts are less effective when there are too many categories, very small differences between data, or when the data isn’t proportional to a whole. In such cases, a bar graph provides clearer comparison and is preferred for data handling in Maths.
9. What are grouped frequency distributions, and how do they simplify data analysis?
Grouped frequency distributions organize data into intervals or classes, making large data sets manageable. By grouping similar values, they help summarize trends and simplify the creation of graphs or further statistical analysis in data handling exercises.
10. How can errors in data collection impact the accuracy of data handling in Mathematics?
Mistakes in data collection—such as recording incorrect values or omitting entries—lead to inaccurate tables and misleading graphs. To ensure precision in Maths, double-check data sources, maintain consistency in methods, and verify entries before analysis and representation.
