Steply

Line of best fit y = 0.5x + 2, points (2, 4), (4, 3), (6, 6), find…

Step by step, with the reason for every step · Residuals · Statistics

Step by step

The question

Question: find the residuals for the line of best fit y = 0.5x + 2 and the points (2, 4), (4, 3) and (6, 6).

The points are the real data.

y = 0.5x + 2; (2, 4), (4, 3), (6, 6)

A residual tells how far a point is from the line.

Residual = actual minus predicted.

Actual is the real y.

Predicted is the y the line gives.

residual = actual − predicted

1 Predict

First we predict each y: x = 2 into the line gives 3.

x = 2 : 0.5(2) + 2 = 1 + 2 = 3

Next: x = 4 into the line gives 4.

x = 4 : 0.5(4) + 2 = 2 + 2 = 4

Next: x = 6 into the line gives 5.

x = 6 : 0.5(6) + 2 = 3 + 2 = 5

2 Actual minus predicted

Careful!

Not predicted minus actual.

That flips the sign.

Actual comes first.

Careful: not 3 − 4 = −1 ✗

Actual minus predicted.

4 minus 3 is 1: 1 above the line.

x = 2 : 4 − 3 = 1

3 minus 4 is −1: 1 below the line.

x = 4 : 3 − 4 = −1

6 minus 5 is 1: 1 above the line.

x = 6 : 6 − 5 = 1

So the residuals are 1, −1, 1.

Positive means above the line, negative means below.

3 Check

Let's check with a picture.

The line of best fit.

The points.

The residual is the distance up or down from the line to the point.

And predicted plus residual gives the actual y: 4, 3, 6.

So the answer is right!

3 + 1 = 4, 4 − 1 = 3, 5 + 1 = 6

Let's look back.

First: predict.

Then: actual minus predicted.

Last: check.

Answer
x = 6 : 6 − 5 = 1

Your turn

Try this one yourself, then check:

Find the residuals for the line of best fit y = 0.5x + 3; (2, 7), (4, 2), (6, 8)
Show the answer
residuals 3, −3, 2

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