NCERT Solutions for Class 6 Maths Chapter 4: Data Handling and Presentation — Complete Guide
Complete step-by-step solutions for all exercises in NCERT Class 6 Maths Chapter 4. Learn to collect, organise, and represent data using tally marks, frequency tables, pictographs, and bar graphs with detailed explanations and practice problems.

Why This Chapter Matters: Data Is Everywhere
We live in the age of data. Every day, you encounter data in newspapers, on TV, on social media, and in everyday conversations. "India scored runs," "The temperature today is C," "Our school has students" — all of these are data. But raw numbers alone do not tell a story. The skill of collecting, organising, and presenting data in a clear and meaningful way is what turns numbers into knowledge.
Chapter 4 of the NCERT Class 6 Maths textbook (2024-25 edition) teaches you exactly this. You will learn how to take messy, unorganised information and transform it into neat frequency tables, vivid pictographs, and clear bar graphs that anyone can understand at a glance.
Why should you care about data handling?
It is a life skill. Whether you become a scientist, a businessperson, a doctor, or a teacher, you will need to collect and interpret data. Understanding graphs and charts is essential for reading newspapers, understanding election results, tracking sports statistics, and making informed decisions.
It develops critical thinking. When you look at a bar graph, you need to ask: What does this graph tell me? What does it NOT tell me? Could the data be misleading? These are critical thinking skills that go far beyond mathematics.
It connects to higher mathematics. Data handling in Class 6 is the foundation for statistics and probability, which you will study in depth in Classes 9 and 10. The concepts of mean, median, mode, and probability all build on what you learn here.
It is highly scoring in exams. Data handling questions are usually straightforward — if you can read a graph and do basic arithmetic, you can score full marks. The key is being systematic and careful with numbers.
In this comprehensive guide, we solve every exercise from Chapter 4, explain the concepts in depth, and give you plenty of practice to build confidence.
Key Concepts and Definitions
Let us establish the vocabulary and concepts you need for this chapter.
What Is Data?
Data is a collection of facts, numbers, or information gathered for a purpose. Data can be:
Qualitative (categorical): Describes qualities or categories that cannot be measured numerically. Examples: favourite colour (red, blue, green), mode of transport (bus, car, bicycle), type of pet (dog, cat, fish).
Quantitative (numerical): Consists of numbers that can be measured or counted. Examples: height ( cm), marks ( out of ), number of siblings ().
Raw data is data that has not been organised or processed. For example, a list of students' favourite fruits written in the order they were asked is raw data. It is hard to draw conclusions from raw data — you need to organise it first.
Organising Data: Tally Marks and Frequency Tables
Tally marks are a quick way to count occurrences. Each occurrence gets one mark (). Every fifth mark crosses the previous four (), making it easy to count in groups of .
A frequency table lists each category (or value) along with how often it occurs (its frequency).
Example: If students' favourite sports are Cricket, Football, Cricket, Tennis, Cricket, Football, Football, Cricket, Tennis, Cricket, the frequency table is:
| Sport | Tally | Frequency | ||||
|---|---|---|---|---|---|---|
| Cricket | $\cancel{ | }$ | ||||
| Football | $ | $ | ||||
| Tennis | $ | $ | ||||
| Total | **** |
The total of all frequencies must equal the total number of data points — this is your verification check.
Pictographs
A pictograph uses pictures or symbols to represent data. Each symbol represents a fixed number of items.
Key elements of a pictograph:
1. Title — tells you what the pictograph is about.
2. Categories — listed in a column or row.
3. Symbols — pictures representing data values.
4. Key (legend) — tells you how many items each symbol represents.
Reading a pictograph: Count the symbols for each category and multiply by the key value.
Drawing a pictograph: Divide each data value by the key value to find how many symbols to draw. If the division is not exact, use a fraction of a symbol (half symbol, quarter symbol).
Choosing the key: The key should be chosen so that the number of symbols is manageable — not too many and not too few. Common choices: items per symbol.
Bar Graphs
A bar graph uses rectangular bars of equal width to represent data. The height (or length) of each bar is proportional to the value it represents.
Key elements of a bar graph:
1. Title — describes what the graph shows.
2. Horizontal axis (x-axis) — shows categories.
3. Vertical axis (y-axis) — shows numerical values (with a scale).
4. Bars — rectangles of equal width, with heights proportional to data values.
5. Scale — the numbering on the y-axis (e.g., unit = students).
6. Gaps — equal spaces between bars.
Advantages of bar graphs over pictographs:
- More precise (you can read exact values from the scale).
- Easier to compare categories (bar heights are easy to compare visually).
- Can handle larger data values without becoming unwieldy.
- No need for fractional symbols.
Choosing the Right Scale
The scale of a bar graph determines how the y-axis is numbered. Choosing the right scale is important:
- If data values range from to , a scale of unit works well (y-axis: ).
- If values range from to , use unit or unit .
- The scale should start at and go up to at least the largest data value.
- All bars should fit comfortably in the available space.
Common mistake: Not starting the y-axis at . This can make small differences look large and is considered misleading.
Exercise 4.1 — Collecting and Organising Data
Exercise 4.1 covers how to collect raw data and organise it into frequency tables using tally marks. The key skill is being methodical — go through the raw data one item at a time, making a tally mark for each.
Solved Example 1: Making a Frequency Table
Problem: The following are the favourite colours of students: Red, Blue, Green, Red, Blue, Red, Green, Blue, Red, Yellow, Blue, Red, Green, Red, Blue, Yellow, Green, Red, Blue, Red.
Organise this data into a frequency table using tally marks.
Solution:
Step 1: Go through the list one by one, making a tally mark for each colour.
Step 2: Count the tally marks for each colour.
| Colour | Tally Marks | Frequency | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Red | $\cancel{ | } | $ | ||||||
| Blue | $\cancel{ | } | $ | ||||||
| Green | $ | $ | |||||||
| Yellow | $ | $ | |||||||
| Total | **** |
Step 3: Verify:
Observations:
- Red is the most popular colour ( students) — this is called the mode.
- Yellow is the least popular ( students).
- More than half the students chose either Red or Blue.
Answer: Frequency table completed. Red is the most popular colour with votes.
Solved Example 2: Interpreting a Frequency Table
Problem: A survey shows the number of siblings students have:
| Siblings | |||||
|---|---|---|---|---|---|
| Students |
(a) How many students were surveyed?
(b) What is the most common number of siblings?
(c) How many students have or more siblings?
Solution:
(a) Total students .
(b) The highest frequency is , corresponding to sibling. So having sibling is most common.
(c) Students with or more siblings .
Answer: (a) students (b) sibling (most common) (c) students.
Solved Example 3: Organising Marks Data
Problem: The marks obtained by students in a test (out of ) are: .
Prepare a frequency table.
Solution:
| Marks | Tally | Frequency | ||||||
|---|---|---|---|---|---|---|---|---|
| $ | $ | |||||||
| $\cancel{ | }$ | |||||||
| $\cancel{ | } | $ | ||||||
| $\cancel{ | } | $ | ||||||
| $ | $ | |||||||
| $ | $ | |||||||
| Total | **** |
Verification:
Observations:
- The most common mark is (frequency ) — this is the mode.
- Only student scored full marks ().
- students () scored or above.
Answer: Frequency table completed. Mode .
Solved Example 4: Grouped Frequency Table
Problem: The heights (in cm) of students are: .
Organise this data into groups of width cm.
Solution:
| Height (cm) | Tally | Frequency | ||||
|---|---|---|---|---|---|---|
| - | $ | $ | ||||
| - | $ | $ | ||||
| - | $ | $ | ||||
| - | $ | $ | ||||
| - | $ | $ | ||||
| - | $ | $ | ||||
| - | $ | $ | ||||
| Total | **** |
Verification:
Why group data? When data has many different values, listing each one separately makes the table too long. Grouping gives a clearer picture of how the data is distributed.
Answer: Grouped frequency table completed. Most students ( out of ) have heights between and cm.
Solved Example 5: Finding Mode from a Table
Problem: The number of goals scored by a football team in matches is given:
| Goals | ||||||
|---|---|---|---|---|---|---|
| Matches |
Find (a) the total goals scored, (b) the mode, (c) the number of matches with fewer than goals.
Solution:
(a) Total goals
goals.
(b) The highest frequency is (for goals). Mode goals.
(c) Matches with fewer than goals: matches.
Answer: (a) goals (b) Mode (c) matches.
Solved Example 6: Conducting Your Own Survey
Problem: Describe how you would collect data on the favourite subjects of students in your class.
Solution:
Step 1: Define the question. "What is your favourite school subject?"
Step 2: List the categories. Maths, Science, English, Social Studies, Hindi, Art/Music, Sports.
Step 3: Collect data. Ask each student and record their answer. Use tally marks on a pre-drawn table.
Step 4: Count and verify. Count tally marks for each subject. Verify that the total equals the number of students asked.
Step 5: Organise into a frequency table.
| Subject | Tally | Frequency | ||||||
|---|---|---|---|---|---|---|---|---|
| Maths | $\cancel{ | } | $ | |||||
| Science | $\cancel{ | }$ | ||||||
| English | $ | $ | ||||||
| ... | ... | ... |
Step 6: Present. Draw a pictograph or bar graph to present your findings.
Tips for good data collection:
- Ask everyone the same question.
- Each person gives exactly one answer.
- Record responses immediately (do not rely on memory).
- Do not influence the answers ("Don't you think Maths is the best?").
Answer: Steps described for conducting a survey on favourite subjects.
Solved Example 7: Two-Way Frequency Table
Problem: In a class of students, like cricket and like football. If like both, how many like neither?
Solution:
Using the inclusion-exclusion principle:
Students who like at least one sport (Cricket) (Football) (Both)
Students who like neither Total At least one
| Like Football | Don't Like Football | Total | |
|---|---|---|---|
| Like Cricket | |||
| Don't Like Cricket | |||
| Total |
Answer: students like neither sport.
Solved Example 8: Mean (Average) from a Frequency Table
Problem: Find the mean of the data:
| Value () | |||||
|---|---|---|---|---|---|
| Frequency () |
Solution:
Mean
Mean
Answer: The mean is .
Practice this topic on SparkEd — free visual solutions and AI coaching
Exercise 4.2 — Pictographs
Exercise 4.2 teaches you to read and draw pictographs. Pictographs are visually appealing and easy to understand, making them ideal for presenting data to a general audience. The key skill is understanding the key (legend) — each symbol represents a fixed number of items.
Solved Example 1: Reading a Pictograph
Problem: A pictograph shows the number of books read by students in a month, where each symbol represents books.
- Anu: 4 symbols
- Bina: 3 symbols
- Charu: 5 symbols
- Dev: 2 symbols
(a) How many books did each student read? (b) Who read the most? (c) Total books read?
Solution:
Since each symbol books:
(a)
- Anu: books
- Bina: books
- Charu: books
- Dev: books
(b) Charu read the most ( books).
(c) Total books.
Answer: (a) Anu: , Bina: , Charu: , Dev: . (b) Charu. (c) books.
Solved Example 2: Pictograph with Half Symbols
Problem: A pictograph shows the number of cars sold by a dealer each month. Each symbol represents cars.
- January: 3 symbols
- February: 2.5 symbols
- March: 4 symbols
- April: 3.5 symbols
How many cars were sold each month? What is the total?
Solution:
- January: cars
- February: cars
- March: cars
- April: cars
Total cars.
Note: The half symbol () represents cars (half of the key value ).
Answer: January: , February: , March: , April: . Total: cars.
Solved Example 3: Drawing a Pictograph
Problem: Draw a pictograph for the following data using a key of symbol students.
| Favourite Fruit | Students |
|---|---|
| Apple | |
| Banana | |
| Mango | |
| Orange | |
| Grapes |
Solution:
Divide each value by to find the number of symbols:
- Apple: symbols
- Banana: symbols
- Mango: symbols
- Orange: symbols
- Grapes: symbols
Favourite Fruits of Students (Key: each symbol students)
| Fruit | Symbols |
|---|---|
| Apple | |
| Banana | |
| Mango | |
| Orange | |
| Grapes |
At a glance, you can see Mango is the most popular and Orange is the least popular.
Answer: Pictograph drawn with key: symbol students.
Solved Example 4: Choosing the Right Key
Problem: The number of trees planted by four classes is: Class A: , Class B: , Class C: , Class D: . Choose an appropriate key and draw a pictograph.
Solution:
Step 1: Look at the data values: . All are multiples of .
Step 2: Choose key: symbol trees.
Step 3: Calculate symbols:
- Class A: symbols
- Class B: symbols
- Class C: symbols
- Class D: symbols
Alternative key: symbol trees would give symbols — this works too, using half symbols.
Answer: Key of trees per symbol works well, giving symbols respectively.
Solved Example 5: Comparing Data from Pictographs
Problem: Two pictographs show the production of two factories. Factory A produces units (shown with symbols) and Factory B produces units (shown with symbols). What is the key? How many more units does Factory B produce?
Solution:
Factory A: symbols units, so each symbol units.
Verify with Factory B: units.
Difference: units (or symbols).
Answer: Key: symbol units. Factory B produces units more.
Solved Example 6: Limitations of Pictographs
Problem: Why might a pictograph not be suitable for the data: City A population , City B , City C ?
Solution:
With a key of symbol people:
- City A: symbols
- City B: symbols
- City C: symbols
This requires drawing many symbols AND using fractional symbols that are hard to draw precisely.
A bar graph would be much more suitable for this data because:
1. You can use a scale on the y-axis to represent large numbers precisely.
2. There is no need for fractional symbols.
3. The exact values can be read from the scale.
Answer: A pictograph is impractical for large numbers with non-round values. A bar graph is more appropriate.
Exercise 4.3 — Bar Graphs: Reading and Interpretation
Exercise 4.3 focuses on reading and interpreting bar graphs. This is a crucial skill — bar graphs are the most common way data is presented in textbooks, newspapers, and reports. You need to be able to extract specific values, compare categories, and draw conclusions from bar graphs.
Solved Example 1: Reading Values from a Bar Graph
Problem: A bar graph shows the marks scored by five students. The y-axis scale goes from to in steps of . The bars show: Asha (), Bala (), Chitra (), Deepak (), Esha (). Answer the following:
(a) Who scored the highest? (b) Who scored the lowest? (c) What is the difference between the highest and lowest marks? (d) How many students scored above ?
Solution:
(a) Deepak scored the highest: marks.
(b) Chitra scored the lowest: marks.
(c) Difference marks.
(d) Students scoring above : Bala (), Deepak (), Esha () students.
Note: Asha scored exactly , which is NOT above .
Answer: (a) Deepak () (b) Chitra () (c) marks (d) students.
Solved Example 2: Scale Interpretation
Problem: In a bar graph, the y-axis shows values . A bar reaches up to the line between and . What value does this bar represent?
Solution:
The line between and is at .
So the bar represents .
Tip: When a bar falls between two gridlines, estimate the value by looking at where it falls. If it is exactly halfway, take the average. If it is closer to one gridline, adjust accordingly.
Answer: The bar represents .
Solved Example 3: Comparing Categories from a Bar Graph
Problem: A bar graph shows the number of students in five different clubs:
| Club | Members |
|---|---|
| Science | |
| Music | |
| Sports | |
| Art | |
| Drama |
(a) Which club has the most members? (b) How many more members does Sports have than Art? (c) What is the total membership across all clubs? (d) What fraction of total members are in the Science club?
Solution:
(a) Sports club has the most members: .
(b) Difference more members.
(c) Total members.
(d) Fraction in Science .
Answer: (a) Sports () (b) more (c) (d) .
Solved Example 4: Identifying Trends from Bar Graphs
Problem: A bar graph shows a city's monthly rainfall (in mm) for January through June: . Describe the trend.
Solution:
The rainfall increases every month:
- Jan to Feb: mm
- Feb to Mar: mm
- Mar to Apr: mm
- Apr to May: mm
- May to Jun: mm
Trend: The rainfall shows a steadily increasing trend from January to June, with the rate of increase also growing. This is consistent with the approach of the monsoon season.
The total rainfall over six months: mm.
June alone accounts for of the total.
Answer: Rainfall increases steadily, with June having the highest rainfall ( mm).
Solved Example 5: Horizontal Bar Graphs
Problem: A horizontal bar graph shows the production of wheat (in thousands of tonnes) by five states. The x-axis goes from to in steps of . State A's bar extends to , State B to , State C to , State D to , State E to .
(a) Which state produces the most wheat? (b) What is the combined production of States B and D? (c) How much more does State E produce than State A?
Solution:
(a) State E produces the most: thousand tonnes.
(b) Combined thousand tonnes (same as State E alone!).
(c) Difference thousand tonnes.
Answer: (a) State E ( thousand tonnes) (b) thousand tonnes (c) thousand tonnes.
Solved Example 6: Misleading Bar Graphs
Problem: A bar graph shows Company A's sales as units and Company B's sales as units. But the y-axis starts at instead of . Why is this misleading?
Solution:
When the y-axis starts at :
- Company A's bar height is units tall.
- Company B's bar height is units tall.
Company B's bar appears three times as tall as Company A's, even though its sales are only higher ( vs. ).
If the y-axis started at :
- Company A's bar would be units tall.
- Company B's bar would be units tall.
Company B's bar would be only taller — a much more accurate visual representation.
Lesson: Always check if the y-axis starts at . A truncated axis can make small differences look dramatic.
Answer: Starting the y-axis at instead of exaggerates the visual difference between the two companies.
Exercise 4.4 — Drawing Bar Graphs
Exercise 4.4 requires you to draw bar graphs from given data. Drawing accurate bar graphs is a skill that requires attention to detail — choosing the right scale, drawing bars of equal width, maintaining equal gaps, and labelling correctly.
Solved Example 1: Drawing a Bar Graph Step by Step
Problem: Draw a bar graph for the following data:
| Mode of Transport | Students |
|---|---|
| Bus | |
| Car | |
| Bicycle | |
| Walk | |
| Auto |
Solution:
Step 1: Choose the scale. Data ranges from to . A scale of unit students works well. Y-axis: .
Step 2: Draw the axes. Horizontal axis for modes of transport. Vertical axis for number of students.
Step 3: Label the axes. X-axis: "Mode of Transport." Y-axis: "Number of Students." Title: "Modes of Transport Used by Students."
Step 4: Draw the bars. Each bar has equal width (say, cm) with equal gaps (say, cm).
- Bus: bar height (reaches the line)
- Car: bar height
- Bicycle: bar height
- Walk: bar height
- Auto: bar height
Step 5: Verify. Check that each bar height matches the data value. Ensure all bars have the same width and equal spacing.
Answer: Bar graph drawn with bars, scale of students per unit.
Solved Example 2: Choosing the Right Scale for Large Values
Problem: Draw a bar graph for the population of five cities (in thousands): Delhi (), Mumbai (), Bangalore (), Chennai (), Kolkata ().
Solution:
Data ranges from to (in thousands). Choose scale: unit thousand.
Y-axis labels: .
Bar heights:
- Delhi: (top of scale)
- Mumbai:
- Bangalore:
- Chennai: (between and gridlines)
- Kolkata: (between and )
Tip for Chennai: Since falls between gridlines, carefully estimate its position (halfway between and ).
Answer: Bar graph drawn with scale of thousand per unit.
Solved Example 3: Double Bar Graph
Problem: The marks of students in Maths and Science are:
| Student | Maths | Science |
|---|---|---|
| Anu | ||
| Bala | ||
| Chitra | ||
| Dev | ||
| Esha |
Draw a double bar graph and compare.
Solution:
A double bar graph shows two bars side by side for each category, using different colours or patterns.
Scale: unit marks. Y-axis: .
For each student, draw two bars:
- Maths bar (e.g., blue): heights
- Science bar (e.g., orange): heights
Observations:
- Anu and Chitra scored higher in Maths than Science.
- Bala, Dev, and Esha scored higher in Science than Maths.
- Chitra has the highest Maths score ().
- Esha has the highest Science score ().
Include a legend showing which colour represents Maths and which represents Science.
Answer: Double bar graph drawn comparing Maths and Science marks.
Solved Example 4: Bar Graph from a Survey
Problem: A class survey on favourite sports gave: Cricket (), Football (), Basketball (), Tennis (), Badminton (). Draw a bar graph and answer: What percentage of students chose Cricket?
Solution:
Total students .
Scale: unit students. Y-axis: .
Percentage choosing Cricket .
Answer: of students chose Cricket. Bar graph drawn with appropriate scale.
Solved Example 5: Reading Between the Lines
Problem: A bar graph shows monthly sales. January: , February: , March: , April: , May: , June: . In which months did sales increase compared to the previous month?
Solution:
Compare each month to the previous:
- Feb () vs. Jan (): Decrease ()
- Mar () vs. Feb (): Increase ()
- Apr () vs. Mar (): Decrease ()
- May () vs. Apr (): Increase ()
- Jun () vs. May (): Decrease ()
Answer: Sales increased in March and May.
Common Mistakes and How to Avoid Them
Here are the most frequent errors students make in data handling problems:
1. Tally Mark Counting Errors
* Mistake: Miscounting tally marks, especially when crossing groups of five.
* Fix: After tallying, count each group of as , add any remaining individual marks, and verify the total matches the number of data points.
2. Forgetting to Verify the Total
* Mistake: Not checking that frequencies sum to the total number of data points.
* Fix: ALWAYS add up all frequencies and confirm they equal the total. This is your safety check.
3. Wrong Key/Scale in Pictographs
* Mistake: Multiplying by the wrong number when reading a pictograph.
* Fix: Always read the key/legend carefully before interpreting the data. If the key says symbol items, multiply the number of symbols by .
4. Unequal Bar Widths or Gaps
* Mistake: Drawing bars of different widths, which makes the graph misleading.
* Fix: All bars must have the same width. All gaps between bars must be equal. Use a ruler and plan your spacing before drawing.
5. Wrong Scale on Bar Graph
* Mistake: Choosing a scale that makes bars too tall or too short.
* Fix: Look at the data range. The scale should give bars between cm and cm tall. If your largest bar would be cm, increase the scale.
6. Not Starting Y-Axis at Zero
* Mistake: Starting the y-axis at a non-zero value without indicating it.
* Fix: Always start at . If values are very large and you need to truncate, use a zigzag break () on the axis to show the break.
7. Misinterpreting Half Symbols in Pictographs
* Mistake: Ignoring half symbols or treating them as full symbols.
* Fix: A half symbol represents half the key value. So if symbol , a half symbol .
Exam Strategy: Scoring Full Marks in Data Handling
Data handling questions are among the most straightforward in the exam. Follow these strategies to ensure you get every mark:
For Frequency Table Questions:
1. Go through the raw data one item at a time — do not skip or rush.
2. Use tally marks (they prevent counting errors).
3. After completing the table, verify that all frequencies sum to the total.
4. If asked for observations, mention the mode (most frequent value) and any interesting comparisons.
For Pictograph Questions:
1. First read the key — what does each symbol represent?
2. Count symbols carefully (including half symbols).
3. Multiply by the key value.
4. For drawing: choose a key that avoids too many or too few symbols (- symbols per category is ideal).
For Bar Graph Reading Questions:
1. Read the scale on the y-axis first.
2. For values between gridlines, estimate carefully.
3. Answer exactly what is asked — "highest," "lowest," "difference," "total."
4. Double-check arithmetic for sums and differences.
For Bar Graph Drawing Questions:
1. Choose an appropriate scale based on the data range.
2. Draw axes with a ruler and label them clearly.
3. Add a title.
4. Make bars of equal width with equal gaps.
5. If possible, verify by re-reading values from your completed graph.
Time Management: Frequency table questions take - minutes. Pictograph and bar graph questions take - minutes. Drawing a bar graph may take minutes — plan accordingly.
Practice on SparkEd's Data Handling page for a variety of data interpretation problems.
Practice Problems — Try These Yourself
Test your data handling skills with these problems:
Problem 1: The blood groups of students are: A, B, O, A, AB, B, O, A, B, B, A, O, AB, A, B, O, A, B, A, O, B, A, O, AB, B, A, O, B, A, O. Prepare a frequency table.
Problem 2: A pictograph shows production of rice in four states. The key is symbol tonnes. State P has symbols. How many tonnes does State P produce?
Problem 3: Draw a bar graph for the number of rainy days in each month: Jan (), Feb (), Mar (), Apr (), May (), Jun ().
Problem 4: From the bar graph: heights of plants are cm. Find the mean height.
Problem 5: A class of students was asked about their favourite season. Summer: , Winter: , Rainy: , Spring: . How many chose Rainy season? What percentage chose Spring?
Problem 6: The runs scored by a batsman in innings are . Represent this data as a bar graph with an appropriate scale.
Problem 7: In a double bar graph showing boys and girls in five classes, Class A has boys and girls, Class B has boys and girls. How many more girls than boys are in Class B?
Problem 8: Explain why a pictograph with key symbol items might be inconvenient. Suggest better key values.
Problem 9: A bar graph's y-axis starts at instead of . The bars show values , , , . Why might this graph give a misleading impression?
Problem 10: Collect data from classmates about their favourite school lunch item. Create a frequency table and draw a bar graph.
Quick Revision Notes
Data Types:
- Qualitative: categories (colours, names, types)
- Quantitative: numbers (marks, heights, counts)
Organising Data:
- Tally marks: groups of ()
- Frequency = how many times a value occurs
- Always verify: sum of frequencies = total data points
Pictograph Rules:
- Each symbol represents a fixed number of items (key)
- Half symbol = half the key value
- Choose key so that number of symbols is manageable (- per category)
Bar Graph Rules:
- Equal width bars with equal gaps
- Y-axis starts at (or use zigzag break)
- Scale should fit the data range
- Must have: title, labelled axes, scale
Comparing Pictographs vs. Bar Graphs:
| Feature | Pictograph | Bar Graph |
|---------|------------|----------|
| Visual appeal | High | Moderate |
| Precision | Low (half symbols) | High (scale) |
| Large data | Impractical | Suitable |
| Drawing effort | Moderate | Low-Moderate |
Key Formulas:
- Mean =
- Percentage =
- Mode = most frequent value
Boost Your Preparation with SparkEd
You have now mastered every exercise in Chapter 4. Data handling is one of the most practical chapters — the skills you learn here will serve you in every subject and in real life.
Here is how SparkEd can help:
- Practice by Difficulty: On our Data Handling practice page, work through Level 1, 2, and 3 problems.
- AI Math Solver: Struggling with a bar graph question or frequency calculation? Paste it into our AI Solver for a clear step-by-step solution.
- AI Coach: Get personalised recommendations on which concepts need more practice.
- Cross-Topic Connections: Data handling connects to Patterns in Mathematics (spotting patterns in data). Explore all chapters on our programs page.
Visit sparkedmaths.com and start practising today!
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