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Study Guide: How to Solve: Box Plots, Cumulative Frequency & Histograms
Source: https://www.fatskills.com/gcse-math/chapter/how-to-solve-box-plots-cumulative-frequency-histograms

How to Solve: Box Plots, Cumulative Frequency & Histograms

By Fatskills Exam Guides Team — the exam nerds behind 28,500+ quizzes and 2.1M practice questions across 500+ global exams.

⏱️ ~5 min read

How to Solve: Box Plots, Cumulative Frequency & Histograms

GCSE & A-Level Maths


Introduction

"Mastering box plots, cumulative frequency, and histograms unlocks 10–15% of your GCSE/A-Level Maths exam marks—enough to boost you a full grade. These graphs help doctors track patient recovery, businesses predict sales, and scientists analyse climate data. Today, you’ll learn the exact steps to draw, interpret, and compare them under exam pressure."


What You Need To Know First

  1. Basic statistics: Mean, median, mode, range, quartiles.
  2. Grouped data: How to read and create frequency tables.
  3. Inequalities: Understanding symbols like and < for class intervals.

Key Vocabulary

Term Plain-English Definition Quick Example
Box plot A graph showing the spread of data using quartiles. Shows min, Q1, median, Q3, max.
Cumulative frequency Running total of frequencies up to a value. If frequencies are 2, 3, 5, cumulative is 2, 5, 10.
Histogram A bar chart for grouped data (bars touch). Bars represent class intervals (e.g., 0–10, 10–20).
Quartiles Values dividing data into four equal parts. Q1 = 25th percentile, Q3 = 75th percentile.
Interquartile Range (IQR) Range of the middle 50% of data. IQR = Q3 – Q1.
Outlier A data point far from the rest. Any value < Q1 – 1.5×IQR or > Q3 + 1.5×IQR.

Formulas To Know

  1. Median position (for cumulative frequency)
  2. Formula: (n + 1) / 2
  3. n = total number of data points.
  4. MEMORISE THIS – Used to find median from cumulative frequency graphs.

  5. Quartile positions

  6. Q1 position: (n + 1) / 4
  7. Q3 position: 3(n + 1) / 4
  8. MEMORISE THIS – Used to find quartiles from cumulative frequency.

  9. Frequency density (for histograms)

  10. Formula: Frequency / Class width
  11. Given on exam sheet – But you must know how to use it.

  12. Outlier boundaries

  13. Lower boundary: Q1 – 1.5 × IQR
  14. Upper boundary: Q3 + 1.5 × IQR
  15. MEMORISE THIS – Used to identify outliers in box plots.

Step-by-Step Method

1. Drawing a Box Plot

Step 1: Order the data from smallest to largest. Step 2: Find the minimum, Q1, median, Q3, and maximum.
- Use the quartile formulas above. Step 3: Draw a number line covering the data range. Step 4: Plot the five key values as vertical lines. Step 5: Draw a box from Q1 to Q3. Step 6: Draw a vertical line inside the box at the median. Step 7: Extend "whiskers" from Q1 to min and Q3 to max. Step 8: Mark any outliers with crosses (×).


2. Drawing a Cumulative Frequency Graph

Step 1: Create a cumulative frequency table.
- Add a column for the upper bound of each class.
- Add a column for cumulative frequency (running total). Step 2: Plot points at (upper bound, cumulative frequency). Step 3: Join points with a smooth curve or straight lines. Step 4: Find the median and quartiles:
- Draw a horizontal line from (n + 1)/2 to the curve, then down to the x-axis.
- Repeat for Q1 and Q3.


3. Drawing a Histogram

Step 1: Check if class widths are equal or unequal. Step 2: Calculate frequency density for each class:
- Frequency density = Frequency / Class width Step 3: Draw axes:
- x-axis = class intervals (bars touch).
- y-axis = frequency density. Step 4: Draw bars with height = frequency density. Step 5: Label axes clearly (include units).


Worked Examples

Example 1 – Basic Box Plot

Data: 3, 5, 7, 8, 9, 10, 12, 15 Step 1: Ordered data: 3, 5, 7, 8, 9, 10, 12, 15 Step 2: Min = 3, Max = 15
- Median = (8 + 9)/2 = 8.5
- Q1 = median of lower half (3, 5, 7, 8) = (5 + 7)/2 = 6
- Q3 = median of upper half (9, 10, 12, 15) = (10 + 12)/2 = 11 Step 3–8: Draw box plot with:
- Whiskers: 3 to 6, 11 to 15
- Box: 6 to 11
- Median line at 8.5

What we did and why: We found the five-number summary (min, Q1, median, Q3, max) to visualise the data’s spread. The box shows the middle 50%, and whiskers show the full range.


Example 2 – Medium Cumulative Frequency Graph

Data: | Time (mins) | Frequency | |-------------|-----------| | 0–10 | 5 | | 10–20 | 12 | | 20–30 | 8 | | 30–40 | 3 |

Step 1: Cumulative frequency table: | Upper Bound | Cumulative Frequency | |-------------|----------------------| | 10 | 5 | | 20 | 17 | | 30 | 25 | | 40 | 28 |

Step 2–3: Plot points (10,5), (20,17), (30,25), (40,28) and join. Step 4: Total data points = 28
- Median position = (28 + 1)/2 = 14.5 → Median ≈ 18 mins
- Q1 position = (28 + 1)/4 = 7.25 → Q1 ≈ 12 mins
- Q3 position = 3(28 + 1)/4 = 21.75 → Q3 ≈ 25 mins

What we did and why: We converted frequencies to a running total to find the median and quartiles. The graph helps estimate values for any percentile.


Example 3 – Exam-Style Histogram

Question: A survey records the number of books read in a year: | Books Read | Frequency | |------------|-----------| | 0–5 | 8 | | 5–15 | 20 | | 15–30 | 12 |

Step 1: Class widths: 5, 10, 15 (unequal). Step 2: Frequency densities:
- 0–5: 8/5 = 1.6
- 5–15: 20/10 = 2.0
- 15–30: 12/15 = 0.8 Step 3–5: Draw bars with heights 1.6, 2.0, 0.8.

What we did and why: We adjusted for unequal class widths using frequency density. The tallest bar (5–15) shows the most common range of books read.


Common Mistakes

  1. MISTAKE: Forgetting to order data before finding quartiles.
    WHY IT HAPPENS: Rushing to calculate without sorting.
    CORRECT APPROACH: Always order data first.

  2. MISTAKE: Drawing histogram bars with gaps.
    WHY IT HAPPENS: Confusing histograms (continuous data) with bar charts (discrete data).
    CORRECT APPROACH: Bars must touch in histograms.

  3. MISTAKE: Using frequency instead of frequency density for unequal class widths.
    WHY IT HAPPENS: Not checking if class widths are equal.
    CORRECT APPROACH: Calculate frequency density if widths differ.

  4. MISTAKE: Misreading cumulative frequency graphs (e.g., using lower bound instead of upper bound).
    WHY IT HAPPENS: Not labelling axes clearly.
    CORRECT APPROACH: Always plot (upper bound, cumulative frequency).

  5. MISTAKE: Incorrectly identifying outliers (e.g., using mean instead of IQR).
    WHY IT HAPPENS: Confusing outlier rules.
    CORRECT APPROACH: Use Q1 – 1.5×IQR and Q3 + 1.5×IQR.


Exam Traps

  1. Trap: "Estimate the median" from a histogram.
    How to Spot it: The question asks for an estimate, not an exact value.
    How to Avoid it: Use the cumulative frequency method or approximate from the tallest bars.

  2. Trap: Comparing box plots with different scales.
    How to Spot it: The x-axes have different ranges.
    How to Avoid it: Check scales first—don’t assume equal ranges.

  3. Trap: "Which group has the highest frequency?" in a histogram with unequal class widths.
    How to Spot it: The tallest bar isn’t always the highest frequency.
    How to Avoid it: Calculate Frequency = Frequency density × Class width to compare.


1-Minute Recap

"Right, listen up—this is your last-minute cheat sheet. For box plots, remember the five-number summary: min, Q1, median, Q3, max. Draw the box from Q1 to Q3, whiskers to min/max, and mark outliers. For cumulative frequency, plot the upper bound against the running total, then read off the median at (n+1)/2. For histograms, if class widths are unequal, use frequency density—height = frequency ÷ width. Common traps? Forgetting to order data, mixing up histograms and bar charts, and misreading scales. Double-check your work, and you’ll smash these questions. Now go ace that exam!