Porisma

Worked solution

Compare a signed dice difference with its absolute value

A fair die is thrown once and XX is its score. Calculate E(X)E(X) and show that Var⁡(X)=35/12\operatorname{Var}(X)=35/12. The die is thrown twice, with scores X1,X2X_1,X_2. Tabulate the distribution of Y=∣X1−X2∣Y=\lvert X_1-X_2\rvert and find E(Y)E(Y). Let Z=X1−X2Z=X_1-X_2. State with reasons, without necessarily evaluating the quantities, whether (a) E(Z2)=E(Y2)E(Z^2)=E(Y^2) and (b) Var⁡(Z)=Var⁡(Y)\operatorname{Var}(Z)=\operatorname{Var}(Y).

[J1978/II/12(modified)]

CJC · Lecture · Example 15

Find the mean of one die

The source die law is

xx123456
P(X=x)P(X=x)1/61/61/61/61/61/61/61/61/61/61/61/6

E(X)=1(1/6)+2(1/6)+3(1/6)+4(1/6)+5(1/6)+6(1/6)=7/2E(X)=1(1/6)+2(1/6)+3(1/6)+4(1/6)+5(1/6)+6(1/6)=7/2. Alternatively symmetry gives (3+4)/2=7/2(3+4)/2=7/2. The Teacher guidance places the main emphasis on the distribution of Y onwards.

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Show the one-die variance

E(X2)=12(1/6)+22(1/6)+32(1/6)+42(1/6)+52(1/6)+62(1/6)=91/6E(X^2)=1^2(1/6)+2^2(1/6)+3^2(1/6)+4^2(1/6)+5^2(1/6)+6^2(1/6)=91/6. Hence Var⁡(X)=E(X2)−[E(X)]2=91/6−(7/2)2=35/12\operatorname{Var}(X)=E(X^2)-[E(X)]^2=91/6-(7/2)^2=35/12, as required.

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Build the complete absolute-difference table

Use the source model of independent fair throws: every ordered pair in the six-by-six table has the same probability 1/361/36, as emphasized in the Teacher note. Rows are X1X_1 and columns X2X_2; each cell is Y=∣X1−X2∣Y=\lvert X_1-X_2\rvert.

X1\X2X_1\backslash X_2123456
1012345
2101234
3210123
4321012
5432101
6543210

Group the equal cell values:

yy012345
P(Y=y)P(Y=y)6/36=1/66/36=1/610/36=5/1810/36=5/188/36=2/98/36=2/96/36=1/66/36=1/64/36=1/94/36=1/92/36=1/182/36=1/18
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Average the absolute difference

E(Y)=0(16)+1(518)+2(29)+3(16)+4(19)+5(118)=35/18E(Y)=0(\frac16)+1(\frac5{18})+2(\frac29)+3(\frac16)+4(\frac19)+5(\frac1{18})=35/18.

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(a) Compare the squares before taking expectations

Z2=(X1−X2)2Z^2=(X_1-X_2)^2 and Y2=∣X1−X2∣2=(X1−X2)2Y^2=\lvert X_1-X_2\rvert^2=(X_1-X_2)^2. They are equal for every outcome, so E(Z2)=E(Y2)E(Z^2)=E(Y^2). The answer is yes.

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(b) Compare the means in the variance formulas

E(Z)=E(X1−X2)=E(X1)−E(X2)=0E(Z)=E(X_1-X_2)=E(X_1)-E(X_2)=0, while E(Y)=E(∣X1−X2∣)>0E(Y)=E(\lvert X_1-X_2\rvert)>0. Thus their means differ. Now Var⁡(Z)=E(Z2)−[E(Z)]2\operatorname{Var}(Z)=E(Z^2)-[E(Z)]^2 and Var⁡(Y)=E(Y2)−[E(Y)]2\operatorname{Var}(Y)=E(Y^2)-[E(Y)]^2. The second moments are equal by (a), but the subtracted squared means differ. Hence the variances are not equal; in fact Var⁡(Z)>Var⁡(Y)\operatorname{Var}(Z)>\operatorname{Var}(Y) (direction made explicit from the source argument).

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Common mistakes

Absolute value changes the distribution and mean but not the squared variable. Do not treat Y as the signed difference. Fairness of each throw alone does not establish the independent-roll model used for the 36 equally likely cells.

Read the hint