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Topic 7 of 7 · Form 4

Bivariate data, scatter diagrams and lines of best fit

Plotting paired data; positive, negative and no correlation; strong and weak correlation; outliers; correlation does not imply causation.

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  1. PDFBivariate data, scatter diagrams and lines of best fit – Statistics notes (Cambridge O Level)45.8 KB

Scatter diagrams

Plotting paired data; positive, negative and no correlation; strong and weak correlation; outliers; correlation does not imply causation.

Line of best fit

  • By eye, passing through the mean point (x̄, ȳ).
  • Method of semi-averages: divide the ordered data into two halves, find the mean point of each half, and draw the line through both points.

Worked example: Data (1, 3), (2, 5), (3, 4), (4, 8), (5, 9), (6, 11). Find the line by semi-averages.

First half mean point (2, 4); second half (5, 28/3 ≈ 9.33)

Gradient = (9.33 − 4) ÷ 3 = 1.78; y = 1.78x + 0.44 (approximately)

Using the line

Interpolation (within the data range) is reasonably reliable; extrapolation (outside) may be unreliable. Interpret the gradient and intercept in context.

Spearman's rank correlation (where required)

rs = 1 − 6Σd² ÷ (n(n² − 1)) for ranked data.

Exam tip: State the meaning of the gradient in context – e.g. "each extra hour of study increases the mark by about 1.8".

Check yourself

  1. What does a negative correlation mean?
  2. Through which point should a line of best fit pass?
  3. Why is extrapolation risky?
Show answers
  1. As one variable increases, the other tends to decrease.
  2. The mean point (x̄, ȳ).
  3. The relationship may not continue beyond the range of the data.
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