Mathematics for Computer Science

(avery) #1

Chapter 19 Deviation from the Mean798


.CC1/^2. So


ExŒC^2 çDp 12 C.1p/ExŒ.CC1/^2 ç

DpC.1p/




ExŒC^2 çC

2


p

C 1





DpC.1p/ExŒC^2 çC.1p/




2


p

C 1





; so

pExŒC^2 çDpC.1p/




2


p

C 1





D


p^2 C.1p/.2Cp/
p

and

ExŒC^2 çD

2 p
p^2

Combining this with (19.7) proves


Lemma 19.3.3.If failures occur with probabilitypindependently at each step, and
Cis the number of steps until the first failure^2 , then


VarŒCçD

1 p
p^2

: (19.8)


19.3.3 Dealing with Constants


It helps to know how to calculate the variance ofaRCb:


Theorem 19.3.4.[Square Multiple Rulefor Variance] LetRbe a random variable
andaa constant. Then
VarŒaRçDa^2 VarŒRç: (19.9)


Proof. Beginning with the definition of variance and repeatedly applying linearity
of expectation, we have:


VarŒaRçWWDExŒ.aRExŒaRç/^2 ç
DExŒ.aR/^2 2aRExŒaRçCEx^2 ŒaRçç
DExŒ.aR/^2 çExŒ2aRExŒaRççCEx^2 ŒaRç
Da^2 ExŒR^2 ç 2 ExŒaRçExŒaRçCEx^2 ŒaRç
Da^2 ExŒR^2 ça^2 Ex^2 ŒRç
Da^2


ExŒR^2 çEx^2 ŒRç




Da^2 VarŒRç (Lemma 19.3.1)

(^2) That is,Chas the geometric distribution with parameterpaccording to Definition 18.4.6.

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