Topic 4.14 · teacher page · Higher Level

The spread does not care where it sits

Why adding a constant changes the mean and not the variance, shown rather than asserted.

The one thing to do with the animation

Slide b and ask them to watch the width bar, not the curve.

The curve slides across the screen and the plus-or-minus one standard deviation bar never changes length. The faint ghost of the original is left in place so the shift is unmistakable.

Then slide a. Now the bar changes, and the mean moves too. Two controls, two different behaviours, and the rule E(aX + b) = aE(X) + b with Var(aX + b) = a²Var(X) stops being two formulas to confuse and becomes a description of what they just watched.

Why a is squared and b disappears

Variance is built from squared distances from the mean. Adding b moves every value and the mean by the same amount, so every distance is unchanged, so the variance is unchanged.

Multiplying by a scales every distance by a, and the squares by a². The square is on the variance and not on the standard deviation, which is why sd(aX + b) is |a|sd(X) with no square at all. The absolute value matters: a negative a flips the distribution and a spread cannot be negative.

The answers

1. E(3X + 5) when E(X) = 43 × 4 + 5 = 17.
2. Var(3X + 5) when Var(X) = 29 × 2 = 18. The 5 contributes nothing.
3. sd(−2X)|−2| × sd(X), so the spread doubles and stays positive.

Where the marks go

1 markApplying a to the mean and adding b, in that order.

1 markSquaring a for the variance and dropping b entirely.

1 markTaking the absolute value for a standard deviation, which is the step a negative a is testing.

What each wrong answer tells you

They giveWhat it means
Variance including bThey applied the mean rule to the variance. The width bar in the widget is the answer; make them watch it again.
Variance with a not squaredConfused the variance rule with the standard deviation rule. Ask which one has units of X and which has units of X squared.
A negative standard deviationThey took −2 straight through. A spread cannot be negative, and that alone should stop them.
Mean unchanged by bRare, but it means they have over-generalised “b does not matter” from the variance rule to everything.

Other things they will say

"Does this work for any distribution?" Yes. These two rules need nothing about shape, which makes them unusually powerful and worth saying explicitly.

"What about X + Y?" Different rule, and it needs independence. Flag it now and do it properly next lesson; conflating the two is a real risk here.

"Why would anyone do this?" Unit changes. Celsius to Fahrenheit is exactly aX + b, and asking what happens to the standard deviation of a set of temperatures makes the rule concrete in one sentence.

A possible order

 What is happening
1Slide b with the instruction to watch only the width bar.
2Slide a. Name both rules from what they saw.
3The squared-distance argument for why b vanishes.
4The three questions, including a negative a.
5A unit conversion question in context, then set up sums of random variables for next lesson.

Two things not to say

Do not teach the two rules as a pair of formulas to memorise. They will be swapped under pressure, and the widget prevents it in two minutes.

Do not skip the negative case. It is where the absolute value lives and it is examined.

Questions to set

Three tiers, ramping the way practice should: the method on its own, then the method inside something real, then a challenge. Set the tier the class in front of you needs rather than one undifferentiated sheet. Answers are given so these can go straight onto a board.

1Fluency

The method on its own, with friendly numbers. Set these first and move on quickly once they are secure.

  1. Unbiased estimateFor the sample 4, 8, 6, 10, 12 give the unbiased estimate of the population variance.
    The mean is 8 and Σ(x − x̅)² = 40, so s² = 40 / 4 = 10.
  2. Linear transformationIf E(X) = 8 and Var(X) = 8, find E(2X + 5) and Var(2X + 5).
    E = 21 and Var = 4(8) = 32.

2In context

The same skill inside a real situation, where the first job is working out what is being asked.

  1. Change of unitsMarks out of 50 are doubled to give a percentage. State what happens to the mean, the standard deviation and the variance.
    Mean doubles, standard deviation doubles, variance multiplies by 4. The variance is in squared units, which is exactly why it is not quoted in reports.
  2. StandardiseA mark of 73 comes from a test with mean 65 and standard deviation 5. Find its standardised value and say what it means.
    z = 1.6, so the mark is 1.6 standard deviations above the mean, which allows comparison with a different test.

3Challenge

Reasoning, working backwards, or spotting an error. These are where the top grades are decided.

  1. Why n minus 1Explain why dividing by n underestimates the population variance.
    The sample mean is itself drawn from the sample, so deviations are measured from the closest possible centre and come out too small. Dividing by n − 1 corrects for the one degree of freedom spent on estimating the mean.
  2. Which does not shiftOf mean, median, standard deviation, IQR and range, which change when every value has 7 added? Explain the pattern.
    Mean and median rise by 7; standard deviation, IQR and range do not change. Measures of location move with the data, measures of spread depend only on differences, and adding a constant leaves every difference alone.

Practicalities

Works on a phone. Nothing is loaded from any other site, so it runs behind a school firewall, and nothing a student does is saved or sent anywhere.