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Pearson Edexcel 4MA1 IGCSE  ·  Topic G4.18

G4.18 Averages from Frequency Tables

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01 — Explanation

What's the difference between a discrete and a grouped frequency table, and why does it matter?

Discrete data lists exact values (e.g. "number of pets") with a frequency for each — because every individual value is known, any average calculated from it is exact. Grouped data uses class intervals (e.g. 10≤t<2010\le t<20) because the data is continuous or too spread out to list individually — since the actual values inside each class are unknown, any mean calculated from it is only an estimate.

02 — Explanation

How do I calculate the mean from a discrete frequency table?

Mean=∑fx∑f\text{Mean} = \frac{\sum fx}{\sum f}
  1. Add a column multiplying each value xx by its frequency ff, to get fxfx.
  2. Sum the frequency column to get ∑f\sum f (the total number of observations), and sum the fxfx column to get ∑fx\sum fx.
  3. Divide: Mean=∑fx÷∑f\text{Mean}=\sum fx \div \sum f.

Example: if ∑fx=35\sum fx=35 and ∑f=20\sum f=20, the mean is 35÷20=1.7535\div20=1.75 — note the mean doesn't need to be a value that actually appears in the data.

03 — Explanation

How do I find the mode and median from the same table?

Mode: the data value xx with the highest frequency — not the frequency number itself, the value it corresponds to.

Median: build a cumulative frequency (CF) column by adding frequencies progressively down the table. Find the median position, (∑f+1)÷2(\sum f+1)\div2, then find which row's CF first reaches that position — the xx-value in that row is the median. If the position isn't a whole number (e.g. the 10.510.5th value), the two middle data values average together.

04 — Explanation

How is the mean of grouped data different — and why is it only an estimate?

Since exact values are unknown within each class, we assume every observation sits exactly at the midpoint of its class: x=lower limit+upper limit2x=\dfrac{\text{lower limit}+\text{upper limit}}{2}. This midpoint stands in for the true (unknown) value in the fxfx calculation. Because real data is rarely spread perfectly evenly around the midpoint, the result is always labelled an estimate, never an exact mean.

Exam Tip

Two errors dominate this calculation: using the class boundary (upper or lower limit) instead of the midpoint for xx, and dividing by the number of classes instead of ∑f\sum f (the true total number of observations). Both produce a meaningless result — always double check your divisor is the total frequency.

05 — Explanation

How do I find the modal class and median class for grouped data?

Modal class: the interval with the highest frequency.

Median class: build the cumulative frequency column, find N/2N/2 (where N=∑fN=\sum f), and identify the first class whose CF exceeds that value — at Foundation level you only need to name this interval, not calculate an exact value inside it.

06 — Explanation

Why is the range of grouped data usually impossible to state exactly?

The true smallest and largest values are hidden somewhere inside the first and last class intervals — you only know the interval they fall in, not the precise number. This is why grouped-data questions rarely, if ever, ask for the range.

07 — Worked example

Worked example

The table shows the time, tt minutes, taken by 30 students to complete a puzzle.

Time (tt)Frequency
0≤t<100 \le t < 106
10≤t<2010 \le t < 2014
20≤t<3020 \le t < 3010

Find an estimate for the mean time, and state the modal class.

  1. Midpoints: 5,15,255, 15, 25.
  2. fxfx values: 6×5=306\times5=30; 14×15=21014\times15=210; 10×25=25010\times25=250.
  3. ∑f=6+14+10=30\sum f = 6+14+10=30. ∑fx=30+210+250=490\sum fx = 30+210+250=490.
  4. Estimated mean =490÷30=16.3=490\div30=16.3 minutes (3 s.f.).
  5. Modal class: highest frequency is 14, so the modal class is 10≤t<2010\le t<20.