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Homework Set #7 solutions Stat 420 Fall 2010 1. #4.62 (a) P(Z 2 < 1 ...

Homework Set #7 solutions Stat 420 Fall 2010 1. #4.62 (a) P(Z 2 < 1 ...

Homework Set #7 solutions Stat 420 Fall 2010 1. #4.62 (a) P(Z 2 < 1 ...

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<strong>Homework</strong> <strong>Set</strong> <strong>#7</strong> <strong>solutions</strong><br />

<strong>Stat</strong> <strong>420</strong> <strong>Fall</strong> <strong>2010</strong><br />

<strong>1.</strong> <strong>#4.62</strong> (a) P (Z 2 < 1) = P (−1 < Z < +1) = .6826 by the tables. (b)<br />

P (−<strong>1.</strong>96 < Z < <strong>1.</strong>96) = .95.<br />

2. #4.64(a) Note that $450 is 2.5 standard deviations above the mean, so<br />

by the table the probability is .0062.<br />

3. #4.81 (a) Γ(1) = ∫ ∞<br />

0 e −y dy = <strong>1.</strong><br />

(b) Γ(α) = ∫ ∞<br />

0 y α−1 e −y dy. Integrating by parts, use dv = e −y dy and<br />

u = y α−1 . Then du = (α − 1)y α−2 dy and v = −e −y , and<br />

Γ(α) = −y α−1 e −y | ∞ 0 + (α − 1)<br />

∫ ∞<br />

0<br />

y α−2 e −y dy = (α − 1)Γ(α − 1).<br />

4. #4.88: Let Y have an exponential distribution with β = 2.4. (a)<br />

P (Y > 3) = 1 ∫ ∞<br />

e −y/2.4 dy = .2865.<br />

2.4 3<br />

(b)<br />

P (2 < Y < 3) = 1 ∫ 3<br />

e −y/2.4 dy = .148<strong>1.</strong><br />

2.4 2<br />

5. #4.90: Let Y = magnitude of the earthquake which is exponential with<br />

β = 2.4. Let X = # of earthquakes that exceed 5.0 on the Richter scale.<br />

Therefore, X is binomial with n = 10 and<br />

p = P (Y > 5) = 1<br />

2.4<br />

∫ ∞<br />

5<br />

e −y/2.4 dy = .1245.<br />

Then if X is the number that exceed 5.0, this is binomial with n=10<br />

and p=.1245, so<br />

P (X ≥ 1) = 1 − P (X = 0) = 1 − (.8755) 10 = .7354<br />

6. #4.104: Y has an exponential distribution with β = 100. Then, P (Y ><br />

200) = e 200/100 = e 2 . Let the random variable X = # of componential<br />

that operate in the equipment for more than 200 hours. Then, X has<br />

a binomial distribution and<br />

P (equipment operates) = P (X ≥ 2) = P (X = 2) + P (X = 3) = .05.


7. #4.110: Y has a gamma distribution with α = 3 and β = .5. Thus,<br />

E(Y) = <strong>1.</strong>5 and V(Y) = .75.<br />

8. #4.126: (a) F (y) = 3y 2 − 2y 3 , =≤ y ≤ <strong>1.</strong> F (y) = 0 for y < 0 and<br />

F (y) = 1 for y > <strong>1.</strong><br />

6 * x * (1 - x)<br />

(b)<br />

0.0 0.5 <strong>1.</strong>0 <strong>1.</strong>5<br />

f(y)<br />

fy<br />

0.0 0.2 0.4 0.6 0.8 <strong>1.</strong>0<br />

F(y)<br />

0.0 0.2 0.4 0.6 0.8 <strong>1.</strong>0<br />

0.0 0.2 0.4 0.6 0.8 <strong>1.</strong>0<br />

(c) P (.5 < Y < .8) = F (.8) − F (.5) = .396.<br />

9. #4.128: On (0, 1), F (y) = 1 − (1 − y) 3 , so we need to solve the cubic<br />

equation 1 − (1 − φ .9 ) 3 = .9 or φ .9 = .5358.... this means the budgeted<br />

cost should be $53.58.<br />

10. #4.130:<br />

E(Y 2 ) =<br />

so<br />

∫<br />

Γ(α + β) 1<br />

y α+1 (1−y) β−1 dy =<br />

Γ(α)Γ(β) 0<br />

V (Y ) = E(Y 2 )−E(Y ) 2 =<br />

Γ(α + β) Γ(α + 2)Γ(β)<br />

Γ(α)Γ(β) Γ(α + 2 + β) = (α + 1)α<br />

(α + β)(α + β + 1) .<br />

( ) 2<br />

(α + 1)α α<br />

(α + β)(α + β + 1) − =<br />

α + β<br />

αβ<br />

(α + β) 2 (α + β + 1) .

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