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NotesMath AATopic 4.4Regression line
Back to Math AA Topics
4.4.22 min read

Regression line

IB Mathematics: Analysis and Approaches • Unit 4

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Contents

  • The regression line of y on x
  • Interpreting the gradient & intercept
  • The mean point lies on the line
  • Two lines & choosing the right one
The best-fit line, straight from the GDC: The regression line of y on x is the best-fit line y = ax + b.

On Paper 2 you get a (gradient) and b (intercept) from the calculator's linear regression — no hand calculation.

The regression line of best fit passes through the mean point (x̄, ȳ); use it to predict y from x.

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IB-style question — find the line

Hours studied x and score y are (1,40), (2,50), (3,55), (4,70), (5,80).

Find the regression line of y on x.

Step by step

  1. Enter the pairs and run linear regression.
  2. Write the line.

Final answer

y = 10x + 29 (to 3 s.f. if needed).

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a = change per unit, b = value at x = 0: In y = ax + b, the gradient a is the change in y for each 1-unit increase in x, and the intercept b is the predicted y when x = 0.

Always read them in context.

IB-style question — interpret a and b

A regression line for plant height y cm against weeks x is y = 1.8x + 4.

Interpret the gradient and the intercept.

Step by step

  1. Gradient = change in y per 1 unit of x.
  2. Intercept = y when x = 0.

Final answer

The plant grows about 1.8 cm per week, and was about 4 cm tall at the start (week 0).

Use the units: State the gradient with units ('per week', 'per °C') and the intercept as the starting value.

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Every regression line passes through (x̄, ȳ): The regression line always passes through the mean point (x̄, ȳ).

So if you know the line and one mean, you can find the other — and the point of the two means is guaranteed to be on the line.

IB-style question — use the mean point

A regression line is y = 10x + 29 and the mean of x is x̄ = 3.

Find the mean of y.

Step by step

  1. The mean point (x̄, ȳ) lies on the line.
  2. Substitute x̄ = 3.

Final answer

ȳ = 59.

A quick check: Substituting (x̄, ȳ) into the regression line should always work exactly — a handy way to check your line.
y on x to predict y; the two lines cross at the mean point: To predict y from x, use the line of y on x; to predict x from y, use x on y.

Both lines pass through (x̄, ȳ), so solving them simultaneously gives the two means.

IB-style question — find the means

The regression line of y on x is y = 2x + 1, and the line of x on y is x = 0.4y + 0.2.

Find the mean of x and the mean of y.

Step by step

  1. Both lines meet at the mean point — solve simultaneously.
  2. Solve for x̄, then ȳ.

Final answer

x̄ = 3, ȳ = 7.

Match the line to the direction: Use the line whose subject is the variable you want to predict — y on x for y, x on y for x.

Using the wrong one loses accuracy and marks.

IB-style question — two regression lines

For a data set, the regression line of y on x is y = 0.8x + 2, and the line of x on y is x = 0.9y − 1.

(a) Which line should be used to estimate y from a given x?

(b) Find the mean point (x̄, ȳ).

Step by step

  1. (a) To predict y FROM x, use the y-on-x line. (Using x-on-y the wrong way round loses marks.)
  2. (b) Both lines pass through the mean point, so solve them simultaneously.
  3. Back-substitute for ȳ.

Final answer

(a) the y-on-x line. (b) mean point ≈ (2.86, 4.29).

The two regression lines cross at the mean point (x̄, ȳ). Use y-on-x to predict y, and x-on-y to predict x — never the other way round.

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A regression line of y on x is y = 0.75x + 6. The mean of x is 12. Find the mean of y. [2 marks]

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