Samuel|Study
Mathematics Statistics & Data Analysis
29 Aug 2026

Spread, box plots and cumulative frequency curves

Saturday, 29 August 2026 · Indigo — tuition · Mathematics · Statistics & Data Analysis

Everything from this session, rebuilt as a study page: the two standard-deviation formulas with the worked numbers, how to read all five values off a box plot, the rules for cumulative frequency curves, and the exact sentence structure the exam wants when you compare two sets of data.

What this lesson covered

Five things, in the order they were taught:

  1. Mean, median and mode — and which one actually represents a set of data when there is an extreme value in it.
  2. Standard deviation — two equivalent formulas, by hand, then the fast calculator route.
  3. Box-and-whisker plots — the five values you must be able to read off in seconds.
  4. Cumulative frequency curves — finding n, reading quartiles, and the "more than" flip.
  5. Comparing two data sets — one measure of average, one measure of spread, written as two sentences.
The whole topic is built on one split: one number for the centre (mean / median / mode) and one number for the spread (range / interquartile range / standard deviation). Almost every question asks you to produce one of each and then say what they mean.
Describing data centre + spread 1 · Centre mean x̄ · median · mode extreme value present → median wins 2 · Spread range · interquartile range · standard deviation bigger spread → less consistent 3 · Displays box-and-whisker → 5 values at a glance cumulative frequency curve → quartiles 4 · Comparing sentence 1: average (median / mean) sentence 2: consistency (IQR / SD)
The four blocks of the topic. Every exam question is somewhere on this map.

1 · Mean, median, mode — which one represents the data?

MeasureHow you get itUse it whenIt lets you down when
Mean (x̄)Add every value, divide by n Data is fairly even, no wild values One extreme value drags it away from where the data actually sits
MedianSort, take the middle position. With an even n, average the two middle values There is an outlier, or the data is skewed You need every value to count (it ignores how far away the extremes are)
ModeThe value that occurs most often Data is categorical, or you want the most common outcome There is no repeat, or several values tie

The worked set from the lesson

Eight values were used all the way through:

5   5   5   6   7   7   8   17
7.5
Mean — 60 ÷ 8
6.5
Median — average of 4th and 5th (6 and 7)
5
Mode — occurs three times
3.74
Standard deviation
The question that was put to the class: mean or median — which better represents this set? The median. The 17 is an outlier: it sits far from every other value and pulls the mean up to 7.5, above seven of the eight numbers. The median, at 6.5, sits where the data actually is.
Trap. With an even number of values the median is the average of the two middle ones, not "the fourth one". With eight values it lives between the 4th and 5th positions.

2 · Standard deviation — the same answer by two roads

Standard deviation answers one question: on average, how far is a value from the mean? Two sets can share a mean and be nothing alike.

Set A — 8, 8, 8, 8 mean 8 · standard deviation 0 · every value identical all four values sit here Set B — 4, 6, 10, 12 mean 8 · standard deviation 3.16 · same centre, wide spread 4 6 mean = 8 for both sets 10 12
The mean cannot tell these two sets apart. The standard deviation can.

Version 1 — deviations from the mean

σ = √( Σ(x − x̄)² ÷ n )

Find how far each value is from the mean, square it (so negatives and positives stop cancelling), average the squares, then square-root back to the original units.

Value xFrequencyx − x̄(x − x̄)²f × (x − x̄)²
53−2.56.2518.75
61−1.52.252.25
72−0.50.250.50
810.50.250.25
1719.590.2590.25
Total8112
σ = √(112 ÷ 8) = √14 = 3.7416… ≈ 3.74
Trap. A value that occurs three times contributes three times. Multiply each squared deviation by its frequency — this is where marks quietly disappear.

Version 2 — mean of the squares minus the square of the mean

σ = √( Σx²/n − x̄² )   "average of the squares − average, squared"

Faster once you already know the mean: square each value, average those, subtract the mean squared.

Value xFrequencyf × x²
532575
613636
724998
816464
171289289
Total8562
σ = √( 562/8 − 7.5² ) = √( 70.25 − 56.25 ) = √14 = 3.74 ✓ same answer

The calculator route — what the lesson said to practise

The exam expects the calculator, not the table. On a ClassWiz-type calculator (the Casio FX-97SG X is the model approved for use in Singapore schools):

  1. SETUP → Statistics → Frequency: ON. Without this you cannot enter "5 occurs 3 times" in one row and you will mis-key long lists.
  2. MENU → Statistics → 1-Variable.
  3. Type the values in the x column and the counts in the FREQ column.
  4. AC, then OPTN → 1-Variable Calc.
  5. Read x̄ = 7.5 and σx = 3.7416…
σx or sx? The calculator gives you both. σx divides by n — that is the one these questions want. sx divides by n − 1 (sample standard deviation) and will be slightly larger. Picking the wrong one costs the mark even though your method was right.

3 · Box-and-whisker plots

A box plot is a picture of five numbers. The lesson's point: you should be able to read all five in a few seconds, because the marks are for what you say about them, not for finding them.

12 25 Min Q₁ (25%) Median (Q₂, 50%) Q₃ (75%) Max Interquartile range = Q₃ − Q₁ — the middle 50% Range = Max − Min = 25 − 12 = 13
The five readings. Quartile positions here are drawn for shape; the lesson's own minimum and maximum were 12 and 25, giving a range of 13.
The trap that was called out twice. The median line does not have to sit halfway across the box. Its position is decided by the data, not by the drawing. A median pushed towards one end tells you the data is skewed — that is information, not a badly drawn diagram.

Why the middle 50% at all?

Because the extremes are the least trustworthy part of a data set — one unusual value can sit far out and say nothing about the group. The interquartile range throws away the outer quarters and measures the part where the data actually lives.

4 · Cumulative frequency curves

0 31 62 93 124 Q₁ median Q₃ the curve ENDS at 124 → n = 124 cumulative frequency value (marks, time, …)
25% of 124 is 31, 50% is 62, 75% is 93. Read across to the curve, then down.
You are asked forWhat you do
How many data values in total (n) Read where the curve ends on the vertical axis — not the largest number on the horizontal axis
MedianGo in at 50% of n, across to the curve, down to the value
Lower quartile Q₁25% of n
Upper quartile Q₃75% of n
Interquartile rangeQ₃ − Q₁ — write down both readings first, then subtract
"How many scored more than 55?"Read the value at 55 (that is the "≤ 55" count), then n − that reading
Every reading off this curve is a "less than or equal to" reading. This is the single biggest source of lost marks in the topic. If the question says more than, you must subtract from the total. The value exactly on the boundary is included in the "≤" side.
A marks tip that came straight from the lesson. When you find an interquartile range, write down the two values you read — for example "Q₃ = 62, Q₁ = 49, IQR = 13" — rather than only the final 13. Graph readings vary slightly between students, so schools accept a range of answers, but only if they can see which readings you took. A bare "13" with no workings gives the marker nothing to accept.

Reading between the gridlines

If your line falls between two gridlines, take the halfway value. Between 52 and 54, read 53. A reading that is a little off is normal; a reading that is wildly off — answering 50 minutes when the whole axis only goes to 10 — means you have misread the axis, and that is worth a second look before you write it down.

The reversed curve, and the trick with two curves

Most cumulative frequency curves rise: they count "≤ this value". Some questions plot the opposite — "number of customers who waited more than t minutes" — and that curve falls. Everything flips: reading across now gives you the "more than" count directly, and it is the "less than" count you have to get by subtracting.

median n ÷ 2 "≤ t" curve — rises "more than t" curve — falls
Where the two curves cross, the count above equals the count below — so that value is the median.

5 · Comparing two sets of data — the answer structure

This is the part that carries the marks, and it has a fixed shape. One sentence about the average, one sentence about the spread, each naming the measure you used and what it means in the context of the question.

SentenceMeasure you quoteWhat it tells the reader
1 — average performanceMedian (or mean) "On average, School A performed better, because its median mark of 40 is higher than School B's 38."
2 — consistency / spreadInterquartile range (or standard deviation) "The two schools were equally consistent, because their interquartile ranges are the same." Or: "School A was less consistent, because its interquartile range is larger, so its marks are more spread out."
Larger spread → more spread out → less consistent. Say all three; the marks are for the interpretation, not for the number.
Never compare a median with a standard deviation. Compare like with like: median against median, IQR against IQR. And always quote the actual figures — a comparison with no numbers in it does not earn the mark.

What happens if everyone's marks change

A favourite follow-up: "5 marks are added to every student's score. What happens to the median? To the interquartile range?"

StatisticAdd c to every valueMultiply every value by k
Mean, median, mode, Q₁, Q₃increase by cmultiply by k
Rangeunchangedmultiply by |k|
Interquartile rangeunchangedmultiply by |k|
Standard deviationunchangedmultiply by |k|
Variance (σ²)unchangedmultiply by k²
Why. Adding the same number to everyone slides the whole data set along the number line. Every value moves, so every measure of position moves with it — but nothing gets closer to or further from anything else, so every measure of spread stays exactly the same.

The traps, in one list

  1. Reading n off the horizontal axis instead of the end of the curve.
  2. Forgetting that every cumulative frequency reading is "≤", so "more than" needs n − reading.
  3. Giving only the final IQR without the two readings it came from.
  4. Forgetting frequency when computing standard deviation by hand.
  5. Using sx instead of σx on the calculator.
  6. Assuming the median sits in the middle of the box.
  7. Quoting the mean when an outlier is present and the median is the honest answer.
  8. Comparing two sets with only one sentence — the spread sentence is a separate mark.
  9. Treating a falling "more than" curve like a normal rising one.

Practice

Work these before looking. They mirror the questions the lesson went through.

1 · For 4, 4, 6, 9, 12, 13 — find the mean, median and standard deviation.

Mean = 48 ÷ 6 = 8. Median = average of 3rd and 4th = (6 + 9) ÷ 2 = 7.5.
Σx² = 16 + 16 + 36 + 81 + 144 + 169 = 462. σ = √(462/6 − 8²) = √(77 − 64) = √13 ≈ 3.61.

2 · A box plot shows min 12, Q₁ 16, median 18, Q₃ 22, max 25. Give the range and the IQR, and say what the median's position tells you.

Range = 25 − 12 = 13. IQR = 22 − 16 = 6.
The median sits 2 above Q₁ but 4 below Q₃, so the lower half of the middle 50% is tighter than the upper half — the data is skewed towards the higher values.

3 · A cumulative frequency curve for 124 students ends at 124. Reading at 55 marks gives 86. How many scored more than 55?

The 86 is the number who scored 55 or fewer. More than 55 = 124 − 86 = 38.

4 · Two classes have median 38 and 40, and both have an interquartile range of 11. Write the comparison.

On average the second class performed better, as its median mark of 40 is higher than the first class's 38. The two classes were equally consistent, as both have an interquartile range of 11, so their marks are equally spread out.

5 · Every student is given 5 bonus marks. State the effect on the median, the range and the standard deviation.

The median increases by 5. The range is unchanged. The standard deviation is unchanged — adding the same amount to everyone shifts the data without spreading it.

6 · A curve is drawn for "number of customers waiting more than t minutes", and a second curve for "waiting t minutes or less" is drawn on the same axes. What does the crossing point give?

The median waiting time. At that point the number waiting longer equals the number waiting less, which is the definition of the middle value.

Worth checking with the teacher

Samuel Study · Mathematics · Statistics and Data Analysis
Lesson of Saturday, 29 August 2026 · Indigo
Built from the session; formulas, worked figures and practice answers independently recomputed.