Probability and Statistics for Engineering and the Sciences
Probability and Statistics for Engineering and the Sciences
9th Edition
ISBN: 9781305251809
Author: Jay L. Devore
Publisher: Cengage Learning
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Chapter 8.4, Problem 51E

A manufacturer of plumbing fixtures has developed a new type of washerless faucet. Let p = P(a randomly selected faucet of this type will develop a leak within 2 years under normal use). The manufacturer has decided to proceed with production unless it can be determined that p is too large; the borderline acceptable value of p is specified as .10. The manufacturer decides to subject n of these faucets to accelerated testing (approximating 2 years of normal use). With X = the number among the n faucets that leak before the test concludes, production will commence unless the observed X is too large. It is decided that if p = .10, the probability of not proceeding should be at most .10, whereas if p = .30 the probability of proceeding should be at most .10. Can n = 10 be used? n = 20? n = 25? What are the actual error probabilities for the chosen n?

Expert Solution & Answer
Check Mark
To determine

Check whether for the given experiment sample size can be used as 10, 20 or 25.

Find the error probabilities for the chosen n.

Answer to Problem 51E

For the given experiment sample n=25 can be used.

The probability of Type I and Type II errors are 0.098 and 0.090 for n=25.

Explanation of Solution

Given info:

A new type of washer less faucet is developed by a manufacturer. Let p be the probability of randomly selected faucet of this type will develop a leak within 2 years under normal use. It was decided that the manufacturer proceed for the production if the value of p is too large. The maximum limit of p is 0.10 for accepting the washer less faucet. Let X be the number among the n faucets that leak before the test procedure concludes. It was decided that if p=0.10, the probability of not proceeding should be at most 0.10. If p=0.30, the probability of proceeding should be at most 0.10.

Calculation:

Let X be the number among the n faucets that leak before the test procedure concludes.

In the experiment for deciding that the manufacturer proceed for the production or not the hypotheses will be,

Null hypothesis:

H0:p=0.10

That is, the probability of randomly selected faucet of this type will develop a leak within 2 years under normal use is 0.10.

Alternative hypothesis:

H0:p>0.10

That is, the probability of randomly selected faucet of this type will develop a leak within 2 years under normal use is more 0.10.

Rejection rule:

Let the null hypothesis will be rejected if the minimum of c number among n faucets that leak before the test procedure concludes that is the null hypothesis will be rejected if Xc

For the sample size of 10 and p=0.10:

Hence, XBin(10,0.1)

For finding the appropriate sample size the Type I error and Type II error should be minimum.

Type I error:

Reject the null hypothesis when actually it is true.

It was decided that if p=0.10, the probability of not proceeding should be at most 0.10 that means Type I error will be maximum 0.10.

In this situation the Type I error will arise if actually the probability of randomly selected faucet of this type will develop a leak within 2 years under normal use is 0.10 but Xc.

Thus,

P(Type I error)=α=P(Xc,when p=0.10)=1P(X<c,when p=0.10)=1P(Xc1,when p=0.10)

Let c=1,

Then,

α=1P(X0)=1B(0;10,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=10
  • Locate p=0.1 corresponding to n=10
  • Find the value corresponding x=0

Hence, B(0;10,0.1)=0.349

Thus,

α=1B(0;10,0.1)=10.349=0.651

Which is very large than 0.10.

Let c=2,

Then,

α=1P(X1)=1B(1;10,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=10
  • Locate p=0.1 corresponding to n=10
  • Find the value corresponding x=1

Hence, B(1;10,0.1)=0.736

Thus,

α=1B(0;10,0.1)=10.736=0.264

Which is very large than 0.10.

Let c=3,

Then,

α=1P(X2)=1B(2;10,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=10
  • Locate p=0.1 corresponding to n=10
  • Find the value corresponding x=2

Hence, B(2;10,0.1)=0.930

Thus,

α=1B(2;10,0.1)=10.930=0.07

Which is less than 0.10.

Hence, Type I error will be less for c=3.

Type II error:

Fail to reject the null hypothesis when actually it is false.

It was decided that if p=0.30, the probability of proceeding should be at most 0.10 that means Type II error will be maximum 0.10.

In this situation the Type II error will arise if actually the probability of randomly selected faucet of this type will develop a leak within 2 years under normal use is more than 0.10 but X<c.

Hence,

P(Type II error)=β=P(X<c,when p=0.30)=P(Xc1,when p=0.30)

In this situation ,XBin(10,0.3).

For c=3,

β=P(X2)=B(2;10,0.3)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=10
  • Locate p=0.3 corresponding to n=10
  • Find the value corresponding x=2

Hence, B(2;10,0.3)=0.383

Thus,

β=B(2;10,0.3)=0.383

Which is quite large value.

Hence, simultaneously the Type I error and Type II error can’t be less for n=10.

Thus, it can be concluded that n=10 can’t be used.

For sample size of 20 and p=0.10:

Hence, XBin(20,0.1)

Thus,

P(Type I error)=α=1P(Xc1,when p=0.10)

Let c=1,

Then,

α=1P(X0)=1B(0;20,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=20
  • Locate p=0.1 corresponding to n=20
  • Find the value corresponding x=0

Hence, B(0;20,0.1)=0.122

Thus,

α=1B(0;20,0.1)=10.122=0.878

Which is very large than 0.10.

Let c=3,

Then,

α=1P(X2)=1B(2;20,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  1. 1. Locate the sample size n=20
  2. 2. Locate p=0.1 corresponding to n=20
  3. 3. Find the value corresponding x=2

Hence, B(2;20,0.1)=0.392

Thus,

α=1B(2;20,0.1)=10.392=0.608

Which is very large than 0.10.

Let c=4,

Then,

α=1P(X3)=1B(3;20,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  1. 1. Locate the sample size n=20
  2. 2. Locate p=0.1 corresponding to n=20
  3. 3. Find the value corresponding x=3

Hence, B(3;20,0.1)=0.867

Thus,

α=1B(3;20,0.1)=10.567=0.133

Which is larger than 0.10.

Let c=5,

Then,

α=1P(X4)=1B(4;10,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  1. 1. Locate the sample size n=20
  2. 2. Locate p=0.1 corresponding to n=20
  3. 3. Find the value corresponding x=4

Hence, B(4;20,0.1)=0.957

Thus,

α=1B(4;20,0.1)=10.957=0.043

Which is less than 0.10.

Hence, Type I error will be less for c=5.

Type II error:

P(Type II error)=β=P(Xc1,when p=0.30)

In this situation ,XBin(20,0.3).

For c=5,

β=P(X4)=B(4;20,0.3)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  1. 1. Locate the sample size n=20
  2. 2. Locate p=0.3 corresponding to n=10
  3. 3. Find the value corresponding x=4

Hence, B(4;20,0.3)=0.238

Thus,

β=B(4;20,0.3)=0.238

Which is quite large value.

Hence, simultaneously the Type I error and Type II error can’t be less for n=20.

Thus, it can be concluded that n=20 can’t be used.

For the sample size of 25 and p=0.10:

Hence, XBin(25,0.1)

Thus,

P(Type I error)=α=1P(Xc1,when p=0.10)

Let c=1,

Then,

α=1P(X0)=1B(0;25,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=25
  • Locate p=0.1 corresponding to n=20
  • Find the value corresponding x=0

Hence, B(0;25,0.1)=0.024

Thus,

α=1B(0;25,0.1)=10.001=0.999

Which is very large than 0.10.

Let c=3,

Then,

α=1P(X2)=1B(2;25,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=25
  • Locate p=0.1 corresponding to n=25
  • Find the value corresponding x=3

Hence, B(2;25,0.1)=0.537

Thus,

α=1B(2;25,0.1)=10.537=0.463

Which is very large than 0.10.

Let c=4,

Then,

α=1P(X3)=1B(3;25,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=25
  • Locate p=0.1 corresponding to n=25
  • Find the value corresponding x=3

Hence, B(3;25,0.1)=0.764

Thus,

α=1B(3;25,0.1)=10.764=0.236

Which is larger than 0.10.

Let c=5,

Then,

α=1P(X4)=1B(4;25,0.1)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=25
  • Locate p=0.1 corresponding to n=25
  • Find the value corresponding x=4

Hence, B(4;25,0.1)=0.214

Thus,

α=1B(4;25,0.1)=10.902=0.098

Which is less than 0.10.

Hence, Type I error will be less for c=5.

Type II error:

P(Type II error)=β=P(Xc1,when p=0.30)

In this situation ,XBin(25,0.3).

For c=5,

β=P(X4)=B(4;25,0.3)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=25
  • Locate p=0.3 corresponding to n=25
  • Find the value corresponding x=4

Hence, B(4;25,0.3)=0.090

Thus,

β=B(4;25,0.3)=0.090

Here, β is less than 0.10.

Hence, simultaneously the Type I error and Type II error will be less for n=20.

Thus, n=25 can be used as the sample size of the given experiment.

The error probabilities for n=25:

From the above calculation, the null hypothesis will be rejected if X5,

P(Type I error)=α=1P(X5,when p=0.10)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=25
  • Locate p=0.1 corresponding to n=25
  • Find the value corresponding x=5

Hence, B(4;25,0.1)=0.902

α=1B(4;25,0.1)=10.902=0.098

Type II error:

P(Type II error)=β=P(X4,when p=0.30)

In this situation ,XBin(25,0.3).

For c=5,

β=P(X4)=B(4;25,0.3)

Where, B(x;n.p)=y=0xb(y;n,p)

Procedure for finding the binomial probabilities value:

From table A.1 of Appendix

  • Locate the sample size n=25
  • Locate p=0.3 corresponding to n=25
  • Find the value corresponding x=4

Hence, B(4;25,0.3)=0.090

Thus,

β=B(4;25,0.3)=0.090

Hence, for n=25 the probability of Type I and Type II errors are 0.098 and 0.090, respectively.

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Probability and Statistics for Engineering and the Sciences

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