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Critical-part failures in NASCAR vehicles. Refer to The Sport Journal (Winter 2007) analysis of critical-part failures at NASCAR races, Exercise 4.144 (p. 277). Recall that researchers found that the time x (in hours) until the first critical-part failure is exponentially distributed with = .10 and s = .10. Now consider a random sample of n = 50 NASCAR races and let represent the sample meantime until the first critical-part failure.

a) Find E() and Var()

b) Although x has an exponential distribution, the sampling distribution of x is approximately normal. Why?

c) Find the probability that the sample meantime until the first critical-part failure exceeds .13 hour.

Short Answer

Expert verified

It is frequently used to simulate the time spent among occurrences. Continuous probability distributions are used to calculate the incidence of occurrences.

Step by step solution

01

 Step 1: (a) Given

The time is exponentially distributed with the mean:

=10=0.10E()==0.10

V()=2=(0.1)2=0.01

The calculation is given below:

Now, represents the sample mean period for n = 50

localid="1651469168306" -=1+2+.......+5050

E(-)=150E(1+2+.......+50)=150(E(1)+E(2)+.......+E(50))=150(++50times+)=5050

localid="1651469270820" =0

E(-)=0.1

localid="1651469378610" V(-)=V(i150i50)=1(50)2V(i150i)=12500i150V(蠂颈)=12500i1502

localid="1651469435234" =125005002=250=0.0150

V(-)=0.0002

02

(b) Explanation

The E(-)=0.1or(-)andV(-)=0.0002=2. Then using the control limit theorem -~N(12)that is-~N(0.001,0.002).It is since n =50 that is the higher size of the sample (>30).

03

(c) Explanation

The calculation is given below:

P(Samplemeantime>0.13)=P(.13)=P(0.010.002>0.130.010.002)=P(z>8.49)=0

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