Library Correlation
Further Mathematics

Correlation

Revise Correlation for Further Mathematics — revision notes and instant AI marking. Free to start.

📖 Revision notes · preview
Edexcel Further Stats 2 · Chapter 2

Correlation

Big idea: Correlation coefficients give you a single number between −1 and 1 that tells you how strongly two things are related — and hypothesis testing tells you whether that relationship is real, or just a fluke in your sample.

Summary — What This Chapter Covers

  • PMCC (r) — measures linear correlation between two continuous, normally distributed variables.
  • Spearman's Rank (rₛ) — a rank-based alternative used when data isn't linear, isn't continuous, or isn't normally distributed.
  • Coding data doesn't change correlation — as long as the coding itself is linear (e.g. subtracting a constant, dividing by a constant).
  • Hypothesis testing for correlation — using your sample's r or rₛ to decide whether there's genuinely a correlation in the whole population, or whether H₀ (no correlation) should be accepted.
  • Always interpret your final answer in context — never just leave a number floating with no meaning attached.

1. Product Moment Correlation Coefficient (PMCC)

Think of PMCC as answering one question: "If I drew a straight line through this scatter of points, how well would that line actually fit?" It only cares about straight-line (linear) relationships, and it only works properly when both variables are continuous and roughly normally distributed — things like height, temperature, or exam marks, rather than categories or rankings.

The result, r, always lands somewhere between −1 and 1:

r valueMeaning
−1Perfect negative linear correlation (as one goes up, the other goes down exactly)
−0.8Strong negative linear correlation
0No linear correlation at all
0.4Weak positive linear correlation
1Perfect positive linear correlation
Intuition check The sign tells you the direction (both go up together, or one goes up as the other goes down). The size (how close to ±1) tells you how tightly the points cluster around a straight line. r = 0 doesn't mean "unrelated" — it just means "not linearly related." There could still be a strong curved relationship!

The Formula

PMCC
r = Sxy / √(Sxx × Syy)
In plain words: r is the "shared variation" between x and y (Sxy), scaled down by how much each variable varies on its own (Sxx and Syy). This scaling is exactly what keeps r trapped between −1 and 1, no matter what units your data is in.
The building blocks (from the formula booklet)
Sxy = Σxy − (ΣxΣy)/n   |   Sxx = Σx² − (Σx)²/n   |   Syy = Σy² − (Σy)²/n
These three quantities always show up together. Get comfortable calculating them from summary statistics (Σx, Σy, Σx², Σy², Σxy) because exam questions almost always hand you those instead of raw data.

Worked Example — Physics vs. Chemistry Marks

  10 students' exam marks are compared
Physics (p)73895655859888634793
Chemistry (c)68914062799476715278

Given: Σp = 747, Σc = 711, Σc² = 53031, Σpc = 55499, and Spp = 3010.1

STEP 1 — Find Scc
Scc = 53031 − (711)²/10 = 2478.9
STEP 2 — Find Spc
Spc = 55499 − (747 × 711)/10 = 2387.3
STEP 3 — Find r
r = 2387.3 / √(3010.1 × 2478.9) = 0.874 (3 s.f.)
STEP 4 — Interpret, in context
Since r is close to +1, there is a strong, positive linear correlation between Physics and Chemistry marks — students who scored highly in Physics tended to score highly in Chemistry too.
Common mistake Never say "there is a correlation" without a reason attached. Examiners want the r value quoted AND a description (strong/weak, positive/negative) tied back to the context of the question — not just the number on its own.
Practice Question 1
For a sample of 8 houses, the correlation between floor area (x, in m²) and sale price (y, in £1000s) is found to have Sxy = 412.5, Sxx = 640.2, Syy = 380.9. Calculate r and interpret it in context.
Practice Question 2
A dataset has Σx = 120, Σy = 340, Σx² = 1780, Σy² = 12200, Σxy = 4150, n = 12. Find Sxx, Syy, Sxy, then r.
Also in the full note
  • 2. Spearman's Rank Correlation Coefficient
  • 3. Hypothesis Testing for Correlation
  • What to Memorise
  • Concepts Checklist
  • Exam Tips
  • Ranking Rules — Read Carefully
  • Worked Example — Two Judges Scoring a Competition
  • Worked Example — Does Sleep Affect Exam Performance?
What's inside
📖 Revision notes ✦ AI flashcards ✓ Instant AI marking

Read the full Correlation notes free

That's the preview — create a free account to read the rest, plus flashcards and practice questions with instant AI marking. No credit card.

Unlock the full notes free →