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Cumulative Frequency IGCSE Extended

Grade 10 · Statistics · Cambridge IGCSE 0580 · Age 14–15

Welcome to Cumulative Frequency!

Cumulative frequency is a powerful statistical tool for analysing large datasets. Instead of working with raw data, you build a running total that lets you estimate medians, quartiles, and percentiles — all essential skills for Cambridge IGCSE 0580 Extended Paper.

Median at n/2  |  LQ at n/4  |  UQ at 3n/4  |  IQR = UQ − LQ  |  Plot at upper class boundary

Learning Objectives

  • Construct cumulative frequency tables from grouped frequency data
  • Plot and draw cumulative frequency curves (S-curves) accurately
  • Read off the median, lower quartile, and upper quartile from a curve
  • Calculate the interquartile range (IQR)
  • Draw and interpret box-and-whisker plots
  • Compare two distributions using median and IQR
  • Find and interpret percentiles from a cumulative frequency curve

CF Tables

Running totals from grouped frequency data

CF Curves

S-shaped curve, plot at upper class boundary

Median & Quartiles

Read off n/2, n/4, 3n/4 positions

IQR

Measure of spread: UQ − LQ

Box Plots

5-number summary: min, LQ, med, UQ, max

Percentiles

p-th percentile at p/100 × n position

Learn 1 — Frequency Tables, CF Tables & Curves

Grouped Frequency Tables

When data is spread over a wide range, we group it into class intervals. Each class has a frequency (the count of values in that interval). The class intervals must not overlap, and together they must cover all the data.

Example: Heights of 60 students (cm)
The table below shows grouped data. Notice each class is written as 140 ≤ h < 150, meaning from 140 (inclusive) up to but not including 150.
Height h (cm)Frequency
140 ≤ h < 1504
150 ≤ h < 16011
160 ≤ h < 17018
170 ≤ h < 18015
180 ≤ h < 1909
190 ≤ h < 2003
Total60

Building a Cumulative Frequency Table

The cumulative frequency for a class is the running total of all frequencies up to and including that class. You add each frequency to the total so far.

Key rule: Cumulative frequency is plotted against the upper class boundary of each interval. For 140 ≤ h < 150, the upper boundary is 150. For 150 ≤ h < 160, it is 160, and so on.
Height h (cm)FrequencyCumulative FrequencyPlot at (upper boundary)
140 ≤ h < 15044150
150 ≤ h < 1601115160
160 ≤ h < 1701833170
170 ≤ h < 1801548180
180 ≤ h < 190957190
190 ≤ h < 200360200
Running total check: The final cumulative frequency must equal the total number of data values (here, 60). If it doesn't, you made an arithmetic error — go back and check each addition.
Always start from zero: Before your first plotted point, you also plot (lower boundary of first class, 0). Here that is (140, 0). This anchors your S-curve correctly at the bottom.

Plotting the Cumulative Frequency Curve

Once you have your CF table, plot cumulative frequency (y-axis) against upper class boundary (x-axis). Then join the points with a smooth curve — this creates the characteristic S-shape (also called an ogive).

Step-by-step plotting:
1. Draw axes: x-axis = values (heights), y-axis = cumulative frequency (0 to 60)
2. Plot each point: (150, 4), (160, 15), (170, 33), (180, 48), (190, 57), (200, 60)
3. Also plot the starting point (140, 0)
4. Join all points with a smooth, continuous S-shaped curve
5. The curve should start gently, steepen in the middle, then flatten at the top
Why S-shaped? Most data clusters in the middle (near the mean). So the curve rises slowly at first, then steeply in the middle (where most values are), then slowly again at the top (fewer extreme values). This is the bell curve "rotated and accumulated."
Do NOT join the points with straight lines (a frequency polygon) — the examiner wants a smooth curve. Use a freehand smooth curve, not a ruler.

Learn 2 — Median, Quartiles & IQR

Reading off the Median

The median is the middle value when all data is arranged in order. For n data values, the median is at the n/2 position on the cumulative frequency axis.

Median position = n/2   |   For n = 60: median at CF = 30
How to read off the median:
1. Calculate n/2 (e.g. 60/2 = 30)
2. On your CF curve, find 30 on the y-axis
3. Draw a horizontal line from 30 to meet the curve
4. From that point, draw a vertical line down to the x-axis
5. Read off the value — this is the median
Always use the curve, not the table. The curve gives you an estimate for grouped data. Show your horizontal and vertical construction lines — examiners reward method marks for these.

Lower and Upper Quartiles

Quartiles divide the data into four equal quarters.

LQ position = n/4   |   UQ position = 3n/4
MeasurePosition on CF axisFor n = 60
Lower Quartile (LQ or Q₁)n/460/4 = 15
Median (Q₂)n/260/2 = 30
Upper Quartile (UQ or Q₃)3n/43×60/4 = 45
Reading quartiles (same technique as median):
— For LQ: go to CF = 15 on y-axis → across to curve → down to x-axis
— For UQ: go to CF = 45 on y-axis → across to curve → down to x-axis
Using our heights example (n = 60):
LQ ≈ 160 cm  |  Median ≈ 168 cm  |  UQ ≈ 178 cm

Interquartile Range (IQR)

The IQR measures the spread of the middle 50% of the data. A smaller IQR means the data is more consistent; a larger IQR means it is more spread out.

IQR = Upper Quartile − Lower Quartile = UQ − LQ
Example: LQ = 160 cm, UQ = 178 cm
IQR = 178 − 160 = 18 cm

This tells us the middle 50% of students have heights within an 18 cm range.
IQR vs Range: The range uses the min and max values, which can be heavily affected by outliers. The IQR is more robust — it ignores the extreme 25% on each side. This makes it a better measure of spread for skewed distributions.
Common error: Some students read the quartile positions as n/4 and 3n/4 but forget to divide properly. For n = 80: LQ is at CF = 20, UQ is at CF = 60. Double-check your arithmetic before drawing the construction lines.

Learn 3 — Box-and-Whisker Plots, Comparison & Percentiles

Box-and-Whisker Plots (Box Plots)

A box-and-whisker plot is a visual summary of a distribution using five key values: the minimum, lower quartile, median, upper quartile, and maximum. These are called the five-number summary.

How to draw a box plot:
1. Draw a number line scaled to cover all your data
2. Draw a box from LQ to UQ
3. Draw a vertical line inside the box at the median
4. Draw whiskers from LQ to the minimum, and from UQ to the maximum

Five-number summary example (heights, n = 60):
Min = 140, LQ = 160, Median = 168, UQ = 178, Max = 200
In exams, the minimum and maximum are usually given in the question or can be read from the CF table (the lower boundary of the first class and upper boundary of the last class). You estimate LQ, median, and UQ from the CF curve.

Comparing Two Distributions

Exam questions often give two groups (e.g. boys and girls, or two schools) and ask you to compare their distributions. You must always compare both average AND spread.

What to compare:
Median: Which group has a higher/lower typical value?
IQR: Which group is more consistent (smaller IQR) or more variable (larger IQR)?
Range: Which group has a greater overall spread (max − min)?
Example comparison statement:
"Group A has a higher median (168 cm) than Group B (162 cm), so Group A is generally taller.
Group A has a smaller IQR (18 cm vs 24 cm), so Group A is more consistent in height."
Must state context: Do not just say "the median is higher." You must say what the median represents in context. Examiners require a comparative statement — "Group A's median is higher than Group B's."

Percentiles

A percentile divides data into hundredths. The p-th percentile is the value below which p% of the data falls. Quartiles are just special percentiles: LQ = 25th percentile, Median = 50th percentile, UQ = 75th percentile.

p-th percentile position on CF axis = (p/100) × n
Example: Find the 90th percentile for n = 60
Position = (90/100) × 60 = 54
Go to CF = 54 on the y-axis → draw across to curve → read off x-axis
The 90th percentile ≈ 187 cm
Number above/below a value:
From the CF curve, you can also find how many values fall below a given x-value.
Example: How many students are shorter than 175 cm?
Go to x = 175 → draw up to curve → read off y-axis ≈ 42 students
Working backwards: If the question asks "what height is exceeded by 10% of students?", that means 90% are below it — so find the 90th percentile as shown above.

Example 1 — Building a CF Table

Q: The times (minutes) taken by 40 students to complete a test are shown. Build the cumulative frequency table.
Time t (min)Freq
20 ≤ t < 303
30 ≤ t < 407
40 ≤ t < 5012
50 ≤ t < 6011
60 ≤ t < 707
M1: Add running totals: 3, 3+7=10, 10+12=22, 22+11=33, 33+7=40
A1:
Upper boundaryCumulative Frequency
303
4010
5022
6033
7040
Check: final CF = 40 = total ✓

Example 2 — Reading Median and Quartiles (n = 40)

Q: From the CF curve above (n = 40), estimate the median, LQ, and UQ.
M1: Median position = 40/2 = 20. From CF = 20 → x-axis → Median ≈ 49 min
M1: LQ position = 40/4 = 10. From CF = 10 → x-axis → LQ ≈ 40 min
M1: UQ position = 3×40/4 = 30. From CF = 30 → x-axis → UQ ≈ 57 min
A1: IQR = UQ − LQ = 57 − 40 = 17 minutes A1

Example 3 — Drawing a Box-and-Whisker Plot

Q: Using the data above (n = 40), draw a box-and-whisker plot. Min = 20, Max = 70.
B1: Five-number summary: Min = 20, LQ = 40, Median = 49, UQ = 57, Max = 70
M1: Draw a scaled number line from 20 to 70
M1: Draw box from 40 to 57, with median line at 49
A1: Draw whiskers: left whisker from 40 to 20, right whisker from 57 to 70

Example 4 — Comparing Two Distributions

Q: Class A: median = 49 min, IQR = 17 min. Class B: median = 44 min, IQR = 22 min. Compare the two classes.
B1: Class A has a higher median (49 min) than Class B (44 min), so Class A typically took longer to complete the test.
B1: Class A has a smaller IQR (17 min vs 22 min), so Class A's times are more consistent / less spread out.
Note: Always make comparative statements — say "higher than Class B", not just "higher".

Example 5 — Finding a Percentile

Q: Using the CF curve for n = 40, find the 80th percentile.
M1: Position = (80/100) × 40 = 32
M1: From CF = 32 on the y-axis → draw horizontal line to curve → draw vertical line to x-axis
A1: 80th percentile ≈ 59 minutes A1
Interpretation: 80% of students completed the test in less than 59 minutes.

Example 6 — How Many Values Exceed a Given Amount

Q: From the CF curve (n = 40), how many students took more than 55 minutes?
M1: From x = 55 on x-axis → draw vertical line up to curve → read off y-axis ≈ 27
M1: 27 students took 55 minutes or less
A1: Students taking more than 55 minutes = 40 − 27 = 13 students A1

Common Mistakes in Cumulative Frequency

These are the errors that cost marks most often in IGCSE exams. Study each one carefully.

Mistake 1 — Plotting at the Midpoint Instead of the Upper Boundary

✗ Wrong: For class 40 ≤ t < 50, plot cumulative frequency at t = 45 (the midpoint)
✓ Correct: Plot cumulative frequency at t = 50 (the upper class boundary)

The cumulative frequency up to a class represents "all values up to the end of that class" — so you plot at the upper boundary. Using the midpoint gives an S-curve shifted to the left and produces wrong estimates for the median and quartiles.

Mistake 2 — Using Wrong Positions for Quartiles

✗ Wrong: For n = 80, the LQ is at CF = 25 (thinking "25th value")
✓ Correct: LQ is at CF = n/4 = 80/4 = 20 (the 20th position)

The positions are n/4 for LQ and 3n/4 for UQ, not n/4 + 1 or other adjustments. For grouped continuous data, use exactly n/4 and 3n/4. Some students confuse this with the discrete data rule where you'd use (n+1)/4 — that rule does not apply here.

Mistake 3 — Not Starting the Curve from Zero

✗ Wrong: First plotted point is (150, 4) — curve starts partway up
✓ Correct: Also plot (140, 0) so the curve starts from zero frequency at the lower boundary of the first class

Without the starting point at (lower boundary, 0), your S-curve will not be anchored correctly and the shape will be wrong at the bottom.

Mistake 4 — Connecting Points with Straight Lines

✗ Wrong: Drawing a series of straight line segments between the plotted points (a polygon)
✓ Correct: Draw a smooth, continuous S-shaped curve through all the points

A CF curve should always be drawn as a smooth freehand curve. Straight lines between points imply the data is uniformly distributed within each class, which is rarely true. You will lose the "smooth curve" mark.

Mistake 5 — Forgetting to Subtract When Finding "How Many Exceed"

✗ Wrong: "How many students scored more than 70?" CF at 70 = 35, answer = 35
✓ Correct: CF at 70 = 35 means 35 scored 70 or less. Answer = total − 35 = n − 35

Cumulative frequency always counts from the bottom up (how many are BELOW or AT a value). To find how many are ABOVE, subtract from the total.

Mistake 6 — Incomplete Comparison Statements

✗ Wrong: "Group A has a higher median." (no comparison to Group B stated)
✓ Correct: "Group A has a higher median (168) than Group B (155), so Group A is generally taller."

When comparing distributions, you must (1) state BOTH values, (2) name both groups, (3) give a contextual interpretation. A standalone statement without comparison earns 0 marks.

Key Formulas — Cumulative Frequency

MeasureFormula / MethodNotes
Cumulative FrequencyRunning total of frequenciesFinal CF = n (total)
Plot positionUpper class boundaryNOT midpoint
Starting point(Lower boundary of first class, 0)Anchors the S-curve
Median positionn/2Read from CF axis
Lower Quartile (LQ) positionn/4Read from CF axis
Upper Quartile (UQ) position3n/4Read from CF axis
Interquartile Range (IQR)IQR = UQ − LQMiddle 50% spread
p-th Percentile position(p/100) × nRead from CF axis
Number exceeding value vn − CF(v)Subtract from total
RangeMax − MinFrom the data/table
Five-number summary: Min  |  LQ  |  Median  |  UQ  |  Max
Box plot width = IQR  |  Whiskers reach to Min and Max

Quick Reference: Quartile Positions for Common n Values

n (total frequency)LQ position (n/4)Median position (n/2)UQ position (3n/4)
40102030
60153045
80204060
100255075
120306090

Comparing Distributions — What to Write

State: median comparison + IQR comparison + contextual meaning
Template: "Group X has a [higher/lower] median ([value]) than Group Y ([value]), so Group X is generally [interpretation]. Group X has a [smaller/larger] IQR ([value] vs [value]), so Group X is [more/less] consistent."

Cumulative Frequency Graph Explorer

Enter up to 6 class intervals with their frequencies. The visualiser will calculate the CF table, draw the S-curve, and read off the median, quartiles, and IQR automatically.

Class width: Start value:
Enter frequencies and click "Draw CF Curve".

Exercise 1 — Building Cumulative Frequency Tables

For each question, a frequency table is given. Enter the missing cumulative frequencies.

1. Complete the CF table. Classes: 0–10 (f=2), 10–20 (f=8), 20–30 (f=15). What is the CF at the end of the third class?

2. Classes: 0–5 (f=4), 5–10 (f=9), 10–15 (f=13), 15–20 (f=6). CF at end of 2nd class?

3. Using Q2's table, CF at end of 3rd class?

4. Using Q2's table, total n (CF at end of 4th class)?

5. Classes: 10–20 (f=6), 20–30 (f=14), 30–40 (f=20), 40–50 (f=10). CF at upper boundary 40?

6. Using Q5's table, total n?

7. The CF values for 5 classes are: 5, 18, 35, 44, 50. What is the frequency of the 3rd class?

8. CF values at boundaries 20, 30, 40, 50, 60 are 4, 15, 28, 37, 40. What is the frequency for the class 40–50?

Exercise 2 — Median and Quartile Positions

For each value of n, calculate the CF axis position to read off each measure.

1. n = 40. At what CF value is the median?

2. n = 40. At what CF value is the LQ?

3. n = 40. At what CF value is the UQ?

4. n = 80. Median position?

5. n = 80. UQ position?

6. n = 100. LQ position?

7. n = 120. Median position?

8. n = 60. For the 80th percentile, at what CF value do you read off?

Exercise 3 — Reading Values from CF Curves

Use the given CF table data (n = 60) to answer the questions. The CF curve passes through: (20,0), (30,3), (40,10), (50,22), (60,33), (70,40), (80,50), (90,60). Use linear interpolation within each class interval.

1. n = 60. Median position?

2. LQ position for n = 60?

3. UQ position for n = 60?

4. The CF at x=50 is 22, and at x=60 is 33. By linear interpolation, estimate the median (at CF=30). Give to 1 d.p.

5. CF at x=40 is 10 (which equals the LQ position). LQ = ?

6. CF at x=70 is 40 (UQ position is 45). Use interpolation between x=70 (CF=40) and x=80 (CF=50). Estimate UQ to 1 d.p.

7. IQR = UQ − LQ. Using LQ=40, UQ=75 from Q5 and Q6.

8. How many values are below x = 50 in this dataset? (Read directly from CF table)

Exercise 4 — Box-and-Whisker Plots & Five-Number Summary

1. Five-number summary: Min=10, LQ=25, Median=35, UQ=50, Max=70. What is the IQR?

2. Five-number summary: Min=5, LQ=20, Median=30, UQ=45, Max=65. What is the range?

3. A box plot has: Min=12, LQ=28, Median=36, UQ=44, Max=60. What is the length of the box?

4. The IQR of a dataset is 18 and the LQ is 32. What is the UQ?

5. From a CF curve (n=50), you read: LQ=24, Median=31, UQ=40. Find the IQR.

6. Box plot: Min=0, Max=100, IQR=30, Median=55, LQ=40. What is the UQ?

7. A distribution has Min=15, Range=65, IQR=20, LQ=38. Find the Median if it is 8 above the LQ.

8. Two groups: Group A IQR=12, Group B IQR=20. Which group is MORE consistent? Enter 1 for A or 2 for B.

Exercise 5 — Mixed Cumulative Frequency Problems

1. A CF table ends: ..., (70, 45), (80, 60). How many values are in the class 70–80?

2. n = 80. At what CF do you read the 90th percentile?

3. From a curve (n=80): CF at x=50 is 72. How many values exceed 50?

4. A CF curve has n=100. LQ=42, UQ=68. IQR = ?

5. n = 100. At what CF do you read the 35th percentile?

6. Frequency table: class 60–70 (f=8), 70–80 (f=14), 80–90 (f=18), 90–100 (f=10). What is n?

7. From Q6's table, the CF at the upper boundary 80 is?

8. Group A: Median=65, IQR=14. Group B: Median=72, IQR=14. Which group has higher typical values? Enter 1 for A, 2 for B.

Practice — 25 Mixed Questions

Non-calc questions are marked with [NC]. All others may use a calculator.

[NC] 1. Frequency table: 0–10(f=5), 10–20(f=12), 20–30(f=8). What is the CF at upper boundary 20?

[NC] 2. n = 60. Median position on CF axis?

[NC] 3. n = 60. LQ position?

[NC] 4. n = 60. UQ position?

[NC] 5. LQ = 28, UQ = 52. IQR = ?

[NC] 6. Cumulative frequencies: 6, 19, 35, 42, 50. What is the frequency of the 4th class?

[NC] 7. Five-number summary: Min=10, LQ=30, Median=45, UQ=60, Max=90. Range = ?

[NC] 8. Same as Q7. IQR = ?

9. n = 120. UQ position?

[NC] 10. CF table ends at (50, 36) and (60, 50). Frequency of class 50–60?

[NC] 11. n = 50. 60th percentile position on CF axis?

[NC] 12. Box plot: LQ=40, IQR=25. UQ = ?

13. From a CF curve (n=80): CF at x=70 is 56. How many values are above 70?

[NC] 14. n = 40. 75th percentile position?

[NC] 15. Frequencies: 4, 10, 18, 12, 6. Total n?

[NC] 16. Cumulative frequency at boundary 3 is 32 and at boundary 4 is 50. Frequency of class 4?

[NC] 17. n = 100. LQ position?

18. From a CF curve (n=100): LQ=45, UQ=73. IQR = ?

[NC] 19. Box plot whisker goes from 20 (min) to LQ=38. Length of left whisker = ?

[NC] 20. The median is at position n/2. For n=90, median position?

21. n = 90. 20th percentile position on CF axis?

[NC] 22. Group A median=58, Group B median=62. Which has higher typical value? Enter 1 for A, 2 for B.

[NC] 23. Group A IQR=15, Group B IQR=22. Which is more consistent? Enter 1 for A, 2 for B.

[NC] 24. For a CF curve, should you plot at the upper class boundary or midpoint? Enter 1 for upper boundary, 2 for midpoint.

[NC] 25. CF values: 8, 20, 38, 50. n = 50. UQ position = 37.5. Using CF=38 at x=40 and CF=20 at x=30, estimate the UQ by interpolation. Give to 1 d.p.

Challenge — 12 Questions (IGCSE Extended Level)

1. A CF curve passes through (50, 0), (60, 8), (70, 26), (80, 44), (90, 56), (100, 60). n=60. By linear interpolation between (70,26) and (80,44), estimate the median (CF=30) to 1 d.p.

2. Using the data in Q1, estimate the LQ (CF=15) by interpolating between (60,8) and (70,26). Give to 1 d.p.

3. Using Q1 data: UQ is at CF=45. Interpolate between (80,44) and (90,56). Estimate UQ to 1 d.p.

4. Using your answers from Q1–Q3, calculate the IQR to 1 d.p.

5. n = 60. Find the 90th percentile position on the CF axis.

6. From Q1's CF curve, estimate the 90th percentile (CF=54) by interpolating between (90,56) and (100,60)? Use: x = 90 + ((54−56)/(60−56))×10. Give to 1 d.p. [Hint: interpolate backwards — CF=54 is BELOW 56].

7. From Q1's data, how many values exceed 85? (Interpolate to find CF at x=85, then subtract from 60.)

8. Two groups both have n=80. Group A: IQR=18. Group B: IQR=27. The median of A=64, median of B=58. Write ONE valid comparison about spread. Enter IQR of the MORE consistent group.

9. A CF table: boundary 30→CF=0, 40→CF=12, 50→CF=35, 60→CF=n. If the median is exactly 50, what must n be? (Median at n/2, and CF at x=50 is 35, so n/2=35.)

10. Box plot: Min=20, Max=90. IQR=24, LQ=38. Find the length of the right whisker (UQ to Max).

11. The 25th and 75th percentiles of a dataset are 36 and 60 respectively. The median is 48. Is the distribution positively skewed, negatively skewed, or symmetric? (Enter 1=positive, 2=negative, 3=symmetric)

12. A dataset has n=200. A student claims the UQ is at CF=150. Is this correct? (Enter 1 for yes, 2 for no — UQ should be at 3n/4=150.)

Exam Style Questions

Mark-scheme style. Show working in your book. Enter final answers for self-marking.

Question 1 — Cumulative Frequency Table & Curve [6 marks]

The table shows the masses (kg) of 80 parcels delivered by a courier.

Mass m (kg)Frequency
0 ≤ m < 16
1 ≤ m < 214
2 ≤ m < 323
3 ≤ m < 419
4 ≤ m < 512
5 ≤ m < 66
(a) Complete the cumulative frequency table. What is the CF at the upper boundary m = 3?
(b) On your CF curve, what CF value do you read off to find the median?
(c) By interpolation between m=2 (CF=20) and m=3 (CF=43), estimate the median to 2 d.p. [median is at CF=40]

Question 2 — Quartiles and IQR [5 marks]

Using the parcel data from Question 1 (n = 80). The CF curve passes through: (1,6), (2,20), (3,43), (4,62), (5,74), (6,80).

(a) What CF value do you read off to find the lower quartile?
(b) Estimate the LQ by interpolating between m=1 (CF=6) and m=2 (CF=20). [LQ at CF=20 — since CF=20 exactly hits boundary m=2, LQ = 2.00 kg]
(c) Estimate the UQ. [UQ at CF=60. Interpolate between m=3 (CF=43) and m=4 (CF=62).]
(d) Calculate the IQR. (UQ − LQ, using your answers above)

Question 3 — Box-and-Whisker Plot [4 marks]

Using the parcel data: Min = 0 kg, Max = 6 kg, LQ = 2.00 kg, Median ≈ 2.70 kg, UQ ≈ 3.89 kg.

(a) What is the length of the box in the box-and-whisker plot? (UQ − LQ, to 2 d.p.)
(b) What is the length of the right whisker? (Max − UQ, to 2 d.p.)

Question 4 — Percentiles and Exceeding a Value [4 marks]

Still using the parcel CF data (n = 80). CF curve: (1,6),(2,20),(3,43),(4,62),(5,74),(6,80).

(a) Find the CF position for the 90th percentile.
(b) Interpolate to estimate the 90th percentile between m=4 (CF=62) and m=5 (CF=74). Give to 2 d.p.
(c) How many parcels have a mass greater than 4 kg? (Use CF at m=4.)

Question 5 — Comparing Two Distributions [5 marks]

The table shows statistics for delivery times (minutes) for two courier companies.

StatisticCompany ACompany B
Minimum1510
Lower Quartile2822
Median3540
Upper Quartile4462
Maximum6090
(a) Calculate the IQR for Company A.
(b) Calculate the IQR for Company B.
(c) Which company has lower (better) typical delivery times? Enter 1 for A, 2 for B.
(d) Which company is more consistent? Enter 1 for A, 2 for B.