NCERT Solutions for Class 8 Maths Chapter 4: Data Handling — Complete Guide
Master pie charts, histograms, grouped frequency tables, and basic probability with 30+ fully solved problems and exam-winning strategies.

Why Data Handling Is One of the Most Practical Chapters
Chapter 4 of NCERT Class 8 Maths — Data Handling — is unique among all the chapters because it connects mathematics directly to the real world. Every time you read a newspaper article with a graph, look at election results on TV, or check your cricket team's batting statistics, you are doing data handling.
This chapter teaches you to organise raw data into meaningful tables, represent data visually through pie charts and histograms, and make predictions using probability. These are skills that are used not just in maths exams, but in science projects, social studies surveys, economics, business, sports analytics, and even daily decision-making.
In Class 8, the chapter builds on your earlier knowledge of bar graphs and tally marks from Classes 6 and 7, and introduces three major new concepts: pie charts (circle graphs), histograms for continuous data, and the foundations of probability. The probability section is especially important as it forms the basis for the full probability chapters in Classes 9 and 10.
This chapter typically carries 5-8 marks in CBSE exams, with pie chart construction and probability calculations being the most commonly asked questions. The good news is that most problems follow straightforward formulas, so with proper practice, this is one of the easiest chapters to score full marks in.
Let us walk through every concept and exercise with detailed solutions!
Organising Data: Frequency Distribution Tables
The first step in data handling is organising raw data into a meaningful format. Raw data is just a collection of numbers — messy and hard to interpret. A frequency distribution table organises this data by counting how often each value (or range of values) appears.
Ungrouped Frequency Distribution
In an ungrouped frequency distribution, each distinct data value gets its own row, and we count how many times it appears (its frequency).
Example: The marks obtained by 20 students in a quiz are: .
| Marks | Tally | Frequency | |||||
|---|---|---|---|---|---|---|---|
| 5 | $\ | \ | \ | \ | $ | 4 | |
| 6 | $\ | \ | \ | $ | 3 | ||
| 7 | $\ | \ | \ | \ | \;\ | $ | 5 |
| 8 | $\ | \ | \ | \ | \;\ | $ | 5 |
| 9 | $\ | \ | \ | $ | 3 | ||
| Total | 20 |
Now we can instantly see that marks and were the most common (mode = and ).
Grouped Frequency Distribution
When data has a wide range of values, we group them into class intervals (also called classes or bins).
Example: Heights (in cm) of 25 students: .
| Class Interval | Frequency |
|---|---|
| 5 | |
| 5 | |
| 5 | |
| 5 | |
| 5 | |
| Total | 25 |
Key Terms:
- Class interval (or class width): The range of each group. Here it is .
- Lower class limit: The smallest value in the interval (e.g., in ).
- Upper class limit: The largest value in the interval (e.g., in ).
- Class mark (midpoint): .
In the convention used in NCERT, the upper limit of one class equals the lower limit of the next (e.g., ). A value like is included in the class , not .
Pie Charts (Circle Graphs): Theory and Construction
A pie chart (or circle graph) is a circular chart divided into sectors, where each sector represents a proportion of the whole. The total of all sectors equals the full circle ().
The Central Angle Formula:
Steps to Draw a Pie Chart:
1. Calculate the total of all values.
2. Find the central angle for each category using the formula above.
3. Verify that all central angles add up to .
4. Draw a circle using a compass.
5. Use a protractor to draw each sector with the correct central angle.
6. Label each sector with the category name and percentage (or value).
Steps to Read a Pie Chart:
1. Identify the category and its central angle (or fraction of the circle).
2. Use the formula: Value .
Pie charts are best used when you want to show the proportion of each category relative to the whole. They are not ideal for comparing values across different time periods — use bar graphs for that.
Solved Example 1: Drawing a Pie Chart
Problem: The following data shows the monthly expenditure of a family. Draw a pie chart.
| Item | Amount (Rs) |
|---|---|
| Food | 3000 |
| Rent | 2400 |
| Education | 1200 |
| Others | 1400 |
Solution:
Total
Central angles:
- Food
- Rent
- Education
- Others
Verification: ✓
Draw a circle, use a protractor to mark sectors with these angles, and label each sector with the category name and amount.
Solved Example 2: Reading a Pie Chart
Problem: A pie chart shows the favourite sports of students. The sector for Cricket has a central angle of , Football has , and Tennis has . How many students chose each sport? What angle does the remaining sector have, and how many students does it represent?
Solution:
Cricket: students.
Football: students.
Tennis: students.
Remaining angle .
Remaining students students.
Verification: ✓
Solved Example 3: Percentage-Based Pie Chart
Problem: A survey of people found that prefer tea, prefer coffee, prefer juice, and the rest prefer milk. Draw a pie chart.
Solution:
Milk percentage .
Central angles:
- Tea
- Coffee
- Juice
- Milk
Verification: ✓
Number of people: Tea , Coffee , Juice , Milk . Total ✓.
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Histograms: Representing Continuous Data
A histogram is a type of bar graph used for continuous grouped data. Unlike regular bar graphs (where bars have gaps between them), histogram bars touch each other because the data is continuous — there are no gaps between class intervals.
How to Draw a Histogram:
1. Mark the class intervals on the x-axis.
2. Mark the frequencies on the y-axis.
3. For each class interval, draw a bar whose height equals the frequency.
4. Bars must touch each other (no gaps).
Key Differences: Bar Graph vs. Histogram
| Feature | Bar Graph | Histogram |
|---|---|---|
| Data type | Discrete/categorical | Continuous/grouped |
| Gaps between bars | Yes | No |
| Bar width | Can be any (equal) | Equals class interval |
| X-axis | Categories | Continuous scale |
| Rearrangement | Bars can be rearranged | Bars cannot be rearranged |
Histograms are especially useful in science experiments where you are measuring continuous quantities like height, weight, temperature, or time.
Solved Example 4: Drawing a Histogram
Problem: The following table shows the marks obtained by students. Draw a histogram.
| Marks | |||||
|---|---|---|---|---|---|
| Students | 4 | 8 | 12 | 10 | 6 |
Solution:
Step 1: Mark class intervals () on the x-axis.
Step 2: Mark frequencies ( to , with suitable scale) on the y-axis.
Step 3: Draw bars:
- : height
- : height
- : height
- : height
- : height
All bars touch each other. The tallest bar corresponds to the class (most students scored in this range).
Total verification: ✓
Solved Example 5: Reading a Histogram
Problem: A histogram shows the weights (in kg) of students in a class. The bars have the following heights: : , : , : , : , : . Find: (a) The total number of students. (b) How many students weigh kg or more? (c) Which class interval has the highest frequency?
Solution:
(a) Total students.
(b) Students weighing kg or more: Classes , , .
students.
(c) The class interval has the highest frequency (), so it is the modal class.
Solved Example 6: Histogram with Unequal Class Intervals
Problem: Draw a histogram for the following data:
| Age (years) | |||||
|---|---|---|---|---|---|
| Number of people | 6 | 8 | 12 | 10 | 9 |
Solution:
The class intervals are unequal: . The minimum class width is .
For histograms with unequal class intervals, we adjust the frequency to frequency density:
- :
- :
- :
- :
- :
Draw bars with these adjusted heights. The widths of the bars will be proportional to the class intervals.
Note: This type of problem is less common in Class 8 CBSE exams but good to know for competitive exams.
Exercise 4.1 — Complete Solutions (Pie Charts and Histograms)
Exercise 4.1 covers construction and interpretation of pie charts, histograms, and frequency distribution tables. Here are detailed solutions for all problem types.
Solved Example 7: Pie Chart for Time Spent
Problem: Priya spends her day as follows: School hours, Homework hours, Play hours, Sleep hours, Others hours. Draw a pie chart.
Solution:
Total hours.
Central angles:
- School
- Homework
- Play
- Sleep
- Others
Verification: ✓
Solved Example 8: Finding Values from a Pie Chart
Problem: In a pie chart showing the colours of cars in a parking lot, the red sector has an angle of , blue has , white has , and black takes the rest. If there are cars in total, how many are black?
Solution:
Angle for black .
Number of black cars .
Answer: There are black cars.
Solved Example 9: Constructing a Grouped Frequency Table
Problem: The marks of students are: . Organise into a grouped frequency table with class intervals of .
Solution:
| Class Interval | Tally | Frequency | ||||||
|---|---|---|---|---|---|---|---|---|
| $\ | \ | $ | 2 | |||||
| $\ | \ | \ | \ | $ | 4 | |||
| $\ | \ | \ | \ | $ | 4 | |||
| $\ | \ | \ | \ | \;\ | \ | $ | 7 | |
| $\ | \ | \ | \ | \;\ | $ | 6 | ||
| $\ | \ | \ | \ | $ | 5 | |||
| $\ | \ | $ | 2 | |||||
| Total | 30 |
The modal class is (highest frequency of ).
Solved Example 10: Histogram to Frequency Table
Problem: A histogram has bars with the following details: (height ), (height ), (height ), (height ), (height ). (a) Write the frequency table. (b) How many data points are there? (c) What fraction of data falls in the range ?
Solution:
(a) Frequency table:
| Class | Frequency |
|---|---|
| 5 | |
| 8 | |
| 15 | |
| 12 | |
| 10 |
(b) Total .
(c) Data in . Fraction .
Probability: Theoretical Foundations
Probability measures how likely an event is to occur. It is a number between and :
- means the event is impossible.
- means the event is certain.
- means the event is possible but not guaranteed.
Key Definitions:
- Experiment: An action that produces a result (e.g., tossing a coin, rolling a die).
- Outcome: A possible result of the experiment (e.g., getting Heads).
- Sample Space: The set of all possible outcomes (e.g., for a coin toss).
- Event: A specific outcome or set of outcomes we are interested in.
- Equally Likely Outcomes: Outcomes that have the same chance of occurring.
The Probability Formula:
Complementary Events:
Probability with Coins
A fair coin has two equally likely outcomes: Heads (H) and Tails (T).
and .
For two coins tossed together, the sample space is: — outcomes.
For three coins: — outcomes.
In general, coins give outcomes.
Probability with Dice
A fair die has six equally likely outcomes: .
Some useful probabilities:
- (outcomes: )
- (outcomes: )
- (outcomes: )
- (outcomes: )
For two dice thrown together, the total outcomes .
Probability with Cards
A standard deck has cards: suits (Hearts, Diamonds, Clubs, Spades) with cards each (A, 2-10, J, Q, K). Hearts and Diamonds are red; Clubs and Spades are black.
-
-
- (J, Q, K of each suit)
-
Exercise 4.2 — Complete Solutions (Probability)
Exercise 4.2 covers probability problems involving coins, dice, balls in bags, and spinner wheels. Here are detailed solutions for all types.
Solved Example 11: Die Probability
Problem: A die is thrown once. What is the probability of getting: (a) a number greater than , (b) a number less than or equal to , (c) the number ?
Solution:
Sample space . Total outcomes .
(a) Greater than : . .
(b) Less than or equal to : . .
(c) The number : (empty set — is not on a die). .
The event is impossible.
Solved Example 12: Balls in a Bag
Problem: A bag contains red balls, blue balls, and green balls. A ball is drawn at random. Find the probability of: (a) a red ball, (b) not a green ball, (c) a blue or green ball.
Solution:
Total balls .
(a) .
(b) .
(c) Blue or green balls . .
Solved Example 13: Experimental Probability
Problem: A coin is tossed times. Heads comes up times. Find the experimental probability of: (a) getting heads, (b) getting tails.
Solution:
(a) .
(b) Tails . .
Note: The theoretical probability of each is . The experimental values are close but not exactly — this is normal. As the number of trials increases, the experimental probability gets closer to the theoretical probability.
Solved Example 14: Two Coins Tossed Together
Problem: Two coins are tossed simultaneously. Find the probability of: (a) both heads, (b) at least one tail, (c) exactly one head.
Solution:
Sample space . Total outcomes .
(a) Both heads: . .
(b) At least one tail: . .
Alternatively: .
(c) Exactly one head: . .
Solved Example 15: Spinner Probability
Problem: A spinner has equal sections numbered to . Find the probability of: (a) getting an odd number, (b) getting a multiple of , (c) getting a number greater than .
Solution:
Total outcomes . All equally likely.
(a) Odd numbers: . .
(b) Multiples of : . .
(c) Greater than : . .
Solved Example 16: Card Probability
Problem: A card is drawn at random from a well-shuffled deck of cards. Find the probability of getting: (a) a red queen, (b) a face card, (c) not a king.
Solution:
(a) Red queens: Queen of Hearts and Queen of Diamonds cards.
.
(b) Face cards: J, Q, K of each suit cards.
.
(c) Kings . Not a king .
.
Alternatively: .
Solved Example 17: Word Probability
Problem: A letter is chosen at random from the word MATHEMATICS. Find the probability that it is: (a) M, (b) a vowel, (c) a consonant.
Solution:
MATHEMATICS has letters: M, A, T, H, E, M, A, T, I, C, S.
(a) M appears times. .
(b) Vowels in MATHEMATICS: A, E, A, I vowels. .
(c) Consonants . .
Verification: ✓
Solved Example 18: Probability of Sum with Two Dice
Problem: Two dice are thrown together. Find the probability that the sum is: (a) , (b) greater than .
Solution:
Total outcomes .
(a) Pairs with sum : outcomes.
.
(b) Pairs with sum (i.e., sum or ):
Sum : outcomes.
Sum : outcome.
Total outcomes.
.
Additional Practice Problems with Solutions
Here are more problems to build your confidence before exams.
Solved Example 19: Pie Chart — Budget Allocation
Problem: A school budget of Rs is allocated as: Teachers' salary , Infrastructure , Sports , Library , Others . Find the central angles and the amount for each.
Solution:
Central angles: Salary , Infrastructure , Sports , Library , Others .
Amounts: Salary , Infrastructure , Sports , Library , Others .
Verification: Angles: ✓. Amounts: ✓.
Solved Example 20: Probability — Multiple Events
Problem: A box contains red, white, and blue marbles. One marble is drawn at random. Find the probability that it is: (a) white, (b) not red, (c) red or blue.
Solution:
Total marbles .
(a) .
(b) .
(c) Red or blue . .
Common Mistakes Students Make in Data Handling
Here are the most frequent errors — avoid these and you will score full marks:
1. **Central angles not adding to :**
* Mistake: Making rounding errors so the angles add to or .
* Fix: Always verify that all central angles sum to exactly before drawing the pie chart. Adjust for rounding if needed.
2. Confusing bar graphs and histograms:
* Mistake: Drawing gaps between bars in a histogram, or drawing bars touching in a bar graph.
* Fix: Histograms (continuous data) = no gaps. Bar graphs (discrete data) = gaps.
3. Wrong class interval convention:
* Mistake: Including a value like in both the class and .
* Fix: In NCERT convention, the upper limit of one class is the lower limit of the next. A value exactly at the boundary (like ) goes in the higher class ().
4. **Probability greater than or negative:**
* Mistake: Getting a probability of and not noticing it is wrong.
* Fix: Probability MUST be between and . If you get a value outside this range, you have made an error.
5. Not simplifying probability fractions:
* Mistake: Writing instead of .
* Fix: Always simplify probability fractions to their lowest terms.
6. Confusing "at least" and "at most":
* Mistake: "At least one head" being interpreted as "exactly one head".
* Fix: "At least one" means one OR more. "At most one" means one OR fewer.
7. Not listing all outcomes for compound events:
* Mistake: Missing outcomes like vs. when two dice are thrown.
* Fix: and are DIFFERENT outcomes. List systematically.
Exam Strategy: How to Score Full Marks in Chapter 4
Chapter 4 is one of the easiest to score full marks in, provided you follow a systematic approach.
Weightage: This chapter typically carries 5-8 marks in CBSE exams across MCQs, construction problems, and probability calculations.
Typical Question Patterns:
* 1 Mark (MCQ/VSA): Simple probability calculation; identifying the type of graph suitable for given data; reading a single value from a pie chart.
* 2-3 Marks (SA): Drawing a pie chart for given data; probability with dice/coins/cards; reading and interpreting a histogram.
* 3-4 Marks (LA): Constructing a pie chart with - categories; multi-part probability problems; converting data to grouped frequency table and drawing histogram.
High-Priority Topics:
1. Pie chart construction (central angle formula)
2. Reading and interpreting pie charts
3. Probability with dice, coins, and balls-in-bag
4. Complementary probability ()
5. Histogram construction for grouped data
Time Allocation: Pie chart problems take - minutes (including drawing). Probability problems take - minutes each.
Pro Tips:
- For pie charts: Calculate ALL angles first, verify they sum to , THEN draw.
- Use a sharp pencil, compass, and protractor for pie charts. Accuracy matters.
- For probability: Always identify the sample space first. Write it out if needed.
- The complement rule () is your best friend for "not" questions.
- Label all graphs clearly with title, axes labels, and scale.
Practice on SparkEd's Data Handling page for exam-ready confidence!
Connections to Other Chapters and Higher Classes
Data handling skills connect to many other areas:
Within Class 8:
- Chapter 7 (Comparing Quantities): Percentage calculations used in pie chart construction.
- Chapter 1 (Rational Numbers): Simplifying probability fractions.
In Class 9:
- Chapter 14 (Statistics): Mean, median, mode, and more advanced frequency distributions.
- Chapter 15 (Probability): A full chapter on probability with more complex problems.
In Class 10:
- Chapter 14 (Statistics): Cumulative frequency, ogives, and median from grouped data.
- Chapter 15 (Probability): Formal probability theory with more complex compound events.
In Real Life:
- Reading election results, sports statistics, stock market charts.
- Conducting science experiments and analysing results.
- Making data-driven decisions in business, medicine, and engineering.
The data handling skills you build now will serve you throughout your academic and professional career!
Boost Your Preparation with SparkEd
You have just gone through the entire Data Handling chapter — pie charts, histograms, frequency tables, and probability. But reading alone will not get you full marks; practice will.
Here is how SparkEd can help:
* Practice by Difficulty: On our Data Handling practice page, work through problems sorted by difficulty.
* AI Math Solver: Stuck on a probability problem or pie chart calculation? Paste it into our AI Solver and get step-by-step solutions.
* AI Coach: Get personalized recommendations on which data handling skills need more practice.
* Cross-Topic Connections: Data Handling connects to Comparing Quantities (Chapter 7) and Rational Numbers (Chapter 1). Explore all chapters on our programs page.
Head over to sparkedmaths.com and start practicing today!
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