Probability And Statistics For Engineering And The Sciences Devore 8th Edition by Jay L. Devore -Test Bank

Probability And Statistics For Engineering And The Sciences Devore 8th Edition by Jay L. Devore -Test Bank

 

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Sample Questions Are Posted Below

 

Chapter 5 – Joint Probability Distributions and Random Samples

 

SHORT ANSWER

 

1. Each front tire on a particular type of vehicle is supposed to be filled to a pressure of 26 psi. Suppose the actual air pressure in each tire is a random variable—X for the right tire and Y for the left tire, with joint pdf

 

 

1. What is the value of K?
2. What is the probability that both tires are underfilled?
3. What is the probability that the difference in air pressure between the two tires is at most 2 psi?
4. Determine the (marginal) distribution of air pressure in the right tire alone.
5. Are X and Y independent random variables?

 

ANS:

 

 

 

 

 

                                       =

                                        = 

               

                                        = .3593  (after much algebra)

 

 

1. is obtained by substituting y for x in (d); clearlyare

not independent.

 

PTS:   1

 

2. Let X denote the number of brand X VCRs sold during a particular week by a certain store. The pmf of X is

 

x	0	1	2	3	4
	.1	.2	.3	.25	.15

 

Seventy percent of all customers who purchase brand X VCRs also buy an extended warranty.  Let Y denote the number of purchasers during this week who buy an extended warranty.

 

1. What is P(X = 4, Y = 2)? [Hint:  This probability equals P(Y = 2/X = 4) P(X = 4); now think of the four purchases as four trials of a binomial experiment, with success on a trial corresponding to buying an extended warranty.]
2. Calculate P(X =Y).
3. Determine the joint pmf of X and Y and then the marginal pmf of Y.

 

ANS:

 

1. For any such pair,

 

 

 

 

 

 

 

 

 

PTS:   1

 

3. Two components of a minicomputer have the following joint pdf for their useful lifetimes X and Y:

 

 

 

 

1. What is the probability that the lifetime X of the first component exceeds 3?
2. What are the marginal pdf”s of X and Y? Are the two lifetimes independent?  Explain.
3. What is the probability that the lifetime of at least one component exceeds 3?

 

ANS:

2. The marginal pdf of X is

It is now clear that f(x,y) is not the product of the marginal pdf”s, so the two random variables are not independent.

 

 

 

 

PTS:   1

 

4. The joint pdf of pressures for right (X) and left (Y) front tires is given by .

 

1. Determine the conditional pdf of Y given that X = x and the conditional pdf of X given that Y = y if you are given
2. If the pressure in the right tire is found to be 22 psi, what is the probability that the left tire has a pressure of at least 25 psi? Compare this to
3. If the pressure in the right tire is found to be 22 psi, what is the expected pressure in the left tire, and what is the standard deviation of pressure in this tire?

 

ANS:

 

 

 

=25.372912

 

 

 

PTS:   1

 

5. An instructor has given a short test consisting of two parts. For a randomly selected student, let X = the number of points earned on the first part and Y = the number of points earned on the second part. Suppose that the joint pmf of X and Y is given in the accompanying table.

 

             

p(x,y)	0	5	10	15
0	.02	.06	.02	.10
5	.04	.15	.20	.10
10	.01	.15	.14	.01

 

 

1. If the score recorded in the grade book is the total number of points earned on the two parts, what is the expected recorded score E(X + Y)?
2. If the maximum of the two scores is recorded, what is the expected recorded score?

 

ANS:

14. + (0 + 5)(.06) + … + (10 + 15)(.01) = 14.10
15. = (0)(.02) + (5)(.06) +…+(15)(.01) = 9.60

 

PTS:   1

 

6. Abby and Bianca have agreed to meet for lunch between noon and 1:00 P.M. Denote Abby’s arrival time by X, Bianca’s by Y, and suppose X and Y are independent with pdf’s.

 

 

 

 

 

What is the expected amount of time that the one who arrives first must wait for the other person?  [Hint:  h(X, Y ) = |X – Y|.]

 

ANS:

 

=

 

PTS:   1

 

7. Show that if X and Y are independent random variables, then

 

ANS:

 

PTS:   1

 

8. Show that if Under what conditions will

 

ANS:

therefore

Corr

 

PTS:   1

 

9. A particular brand of dishwasher soap is sold in three sizes:  25oz, 40oz, and 65 oz. Twenty percent of all purchasers select a 25 oz box, fifty percent select a 40 oz box, and the remaining thirty percent choose a 65 oz box. Let  denote the package sizes selected by two independently selected purchasers.

 

1. Determine the sampling distribution of , calculate , and compare to
2. Determine the sampling distribution of the sample variance

 

ANS:

 

		20	.50	.30
		25	40	65
.20	25	.04	.10	.06
.50	40	.10	.25	.15
.30	65	.06	.15	.09

	25	32.5	40	45	52.5	65
	.04	.20	.25	.12	.30	.09

 

 

	0	112.5	312.5	800
	.38	.20	.30	.12

 

 

PTS:   1

 

10. It is known that 80% of all brand A zip drives work in a satisfactory manner throughout the warranty period (are “success”). Suppose that n = 10 drives are randomly selected.  Let X = the number of successes in the sample. The statistic X/n is the sample proportion (fraction) of successes. Obtain the sampling distribution of this statistic.  [Hint:  One possible value of X/n is .3, corresponding to X = 3. What is the probability of this value (what kind of random variable is X)?]

 

ANS:

 

x	0	1	2	3	4	5	6	7	8	9	10
x/n	0	.1	.2	.3	.4	.5	.6	.7	.8	.9	1.0
p(x/n)	.000	.000	.000	.001	.005	.027	.088	.201	.302	.269	.107

 

X is a binomial random variable with p = .8.

 

PTS:   1

 

11. Let X be the number of packages being mailed by a randomly selected customer at a certain shipping facility.  Suppose the distribution of X is as follows:

 

x	1	2	3	4
p(x)	.4	.3	.2	.1

 

1. Consider a random sample of size n = 2 (two customers), and let be the sample mean number of packages shipped.  Obtain the probability distribution of .
2. Refer to part (a) and calculate
3. Again consider a random sample of size n = 2, but now focus on the statistic R = the sample range (difference between the largest and smallest values in the sample). Obtain the distribution of R. [Hint:  Calculate the value of R for each outcome and use the probabilities from part (a).]
4. If a random sample of size n = 4 is selected, what is ? (Hint:  You should not have to list all possible outcomes, only those for which

 

ANS:

 

Outcome	1,1	1,2	1,3	1,4	2,1	2,2	2,3	2,4
Probability	.16	.12	.08	.04	.12	.09	.06	.03
	1	1.5	2	2.5	1.5	2	2.5	3
	0	1	2	3	1	0	1	2

 

 

Outcome	1,1	3,2	3,3	3,4	4,1	4,2	4,3	4,4
Probability	.08	.06	.04	.02	.04	.03	.02	.01
	2	2.5	3	3.5	2.5	3	3.5	4
	2	1	0	1	3	2	1	2

 

	1	1.5	2	2.5	3	3.5	4
	.16	.24	.25	.20	.10	.04	.01

 

 

c.

	0	1	2	3
	.30	.40	.22	.08

 

P(2,2,1,1) + P (3,1,1,1)  +…+P(1,1,1,3)

 

 

PTS:   1

 

12. A company maintains three offices in a certain region, each staffed by two employees. Information concerning yearly salaries (1000’s of dollars) is as follows:

 

 

Office	1	1	2	2	3	3
Employee	1	2	3	4	5	6
Salary	19.7	23.6	20.2	23.6	15.8	19.7

 

1. Suppose two of these employees are randomly selected from among the six (without replacement). Determine the sampling distribution of the sample mean salary
2. Suppose one of the three offices is randomly selected. Let denote the salaries of the two employees. Determine the sampling distribution of
3. How does from parts (a) and (b) compare to the population mean salary

 

ANS:

	17.75	18.0	19.7	19.95	21.65	21.9	23.6

b.

	17.75	21.65	21.9
	1/3	1/3	1/3

 

20. all three values are the same: 20.4333

 

 

 

 

PTS:   1

 

13. The breaking strength of a rivet has a mean value of 10,000 psi and a standard deviation of 500     psi.

 

1. What is the probability that the sample mean breaking strength for a random sample of 40 rivets is between 9950 and 10,250?
2. If the sample size had been 15 rather than 40, could the probability requested in part (a) be calculated from the given information?

 

ANS:

 

1. n = 40

 

 

=.9992 – .2643 =.7349

1. According to the Rule of Thumb given in your text, n should be greater than 30 in order to

apply the C.L.T., thus using the same procedure for n = 15 as was used for n = 40 would not  appropriate.

 

PTS:   1

 

14. The lifetime of a certain type of battery is normally distributed with mean value 12 hours and standard deviation 1 hour. There are four batteries in a package. What lifetime value is such that the total lifetime of all batteries in a package exceeds that value for only 5% of all packages?

 

ANS:

X is normally distributed with   Sample size n = 4.

 

We desire the 95^th percentile:  48 + (1.645)(2) = 51.29

 

PTS:   1

 

15. The number of parking tickets issued in Grand Rapids on any given weekday has a Poisson distribution with parameter What is the approximate probability that
16. Between 40 and 70 tickets are given out on a particular day? (Hint:  When is large, a Poisson random variable has approximately a normal distribution.)
17. The total number of tickets given out during a 5-day week is between 215 and 265?

 

ANS:

1. With Y = # of tickets, Y has approximately a normal distribution with
2. Here

 

 

PTS:   1

 

16. Let  represent the times necessary to perform three successive repair tasks at a certain service facility. Suppose they are independent normal random variables with expected values     respectively.

 

1. If

Calculate   What is

1. Using the given in part (a), calculate
2. Using the given in part (a), calculate
3. If calculate

 

 

ANS:

 

 

 

 

 

 

 

  

 

We want

 

 

 

 

PTS:   1

 

17. Suppose your waiting time for a bus in the morning is uniformly distributed on [0,5], whereas waiting time in the evening is uniformly distributed on [0,10] independent of morning waiting time.

 

1. If you take the bus each morning and evening for a week, what is your total expected waiting time? [Hint: Define random variables  and use a rule of expected value.)
2. What is the variance of your total waiting time?
3. What are the expected value and variance of the difference between morning and evening waiting times on a given day?
4. What are the expected value and variance of the difference between morning waiting time and total evening waiting time for a particular week?

 

ANS:

Let  denote morning times and denote evening times.

 

 

 

 

 

PTS:   1

 

18. Three different roads feed into a particular freeway entrance. Suppose that during a fixed time period, the number of cars coming from each road onto the freeway is a random variable, with expected value and standard deviation as given in the table.

 

 

	Road 1	Road 2	Road 3
Expected value	750	1000	550
Standard deviation	16	24	18

 

1. What is the expected total number of cars entering the freeway at this point during the period? (Hint:  Let
2. What is the variance of the total number of entering cars? Have you made any assumptions about the relationship between the numbers of cars on the different roads?
3. With denoting the number of cars entering from road I during the period, suppose that

(so that the three streams of traffic are not independent).  Compute the expected total number of entering cars and the standard deviation of the total.

 

ANS:

2300. = 750 + 1000 + 550 = 2300.
2301. Assuming independence of
2302. =1696, with standard

deviation = 41.1825

 

PTS:   1

 

19. In an area having sandy soil, 50 small trees of a certain type were planted, and another 50 trees were planted in an area having clay soil. Let X = the number of trees planted in sandy soil that survive 1 year and Y = the number of trees planted in clay soil that survive 1 year. If the probability that a tree planted in sandy soil will survive 1 year is .7 and the probability of 1-year survival in clay soil is .6, compute an approximation to (do not bother with the continuity correction).

 

ANS:

X is approximately normal with  as is

Y with

 

PTS:   1