/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q15E Many manufacturers have quality ... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

Many manufacturers have quality control programs that include inspection of incoming materials for defects. Suppose a computer manufacturer receives circuit boards in batches of five. Two boards are selected from each batch for inspection. We can represent possible outcomes

of the selection process by pairs. For example, the pair (1, 2) represents the selection of boards 1 and 2 for inspection.

a. List the ten different possible outcomes.

b. Suppose that boards 1 and 2 are the only defective boards in a batch. Two boards are to be chosen at random. Define X to be the number of defective boards observed among those inspected. Find the probability distribution of X.

c. Let F(x) denote the cdf of X. First determine \(F\left( 0 \right) = P\left( {X \le 0} \right)\), F(1), and F(2); then obtain F(x) for allother x.

Short Answer

Expert verified

a. The ten different possible outcomes are\(\left( {1,2} \right),\left( {1,3} \right),\left( {1,4} \right),\left( {1,5} \right),\left( {2,3} \right),\left( {2,4} \right),\left( {2,5} \right),\left( {3,4} \right),\left( {3,5} \right),\left( {4,5} \right)\)

b.The probability distribution of X is

X

P(X)

0

0.30

1

0.60

2

0.10

c. The cumulative distribution of X is

\(F\left( x \right) = \left\{ \begin{array}{l}0,\,\,\,\,\,\,\,\,\,\,{\rm{when}}\,x < 0\\0.3\,\,\,\,\,\,\,\,{\rm{when}}\,0 \le x < 1\\0.9\,\,\,\,\,\,\,\,{\rm{when}}\,1 \le x < 2\\0.1\,\,\,\,\,\,\,\,\,{\rm{when}}\,x \ge 2\end{array} \right.\)

Step by step solution

01

Given information

Two circuit boards are selected from each five batches for inspection of incoming materials for defects.

02

List the ten different possible outcomes

a.

There is selection of two boards from each batch having five boards in order to find the possible outcomes.

As order does not matter, use combination formula to find the number of ways that two boards are drawn from each batch of 5 boards.

\(^n{C_r} = \frac{{n!}}{{r!\left( {n - r} \right)!}}\)

Here, the total number of objects are,\(n = 5\)and the number of choosing objects,\(r = 2\).

\(\begin{aligned}^5{C_2} &= \frac{{5!}}{{2!\left( {5 - 2} \right)!}}\\ &= \frac{{5 \times 4 \times 3!}}{{\left( {2!} \right)\left( {3!} \right)}}\\ &= 10\end{aligned}\)

The 10 possible outcomes of the selection process are described by pairs as follows:

\(\left( {1,2} \right),\left( {1,3} \right),\left( {1,4} \right),\left( {1,5} \right),\left( {2,3} \right),\left( {2,4} \right),\left( {2,5} \right),\left( {3,4} \right),\left( {3,5} \right),\left( {4,5} \right)\)

Here, the pair (1,2) represent the selection of boards 1 and 2.

03

Determine the probability distribution of X.

b.

Out of 5 boards in a batch, only board 1 and 2 are defective so to compute the probability\(P\left( {X = 0} \right)\), avoid the pairs that consist of board 1 and board 2 from 10 possible pairs.

The remaining pairs are\(\left\{ {\left( {3,4} \right),\left( {3,5} \right),\left( {4,5} \right)} \right\}\).

So, the probability is computed as,

\(\begin{aligned}P\left( {X = 0} \right) &= \frac{3}{{10}}\\ &= 0.30\end{aligned\)

Similarly, compute the probability\(P\left( {X = 1} \right)\). In this case, either one of the pair is board 1 or board 2.

The possible pairs are\(\left\{ {\left( {1,3} \right),\left( {1,4} \right),\left( {1,5} \right),\left( {2,3} \right),\left( {2,4} \right),\left( {2,5} \right)} \right\}\).

So, the probability is computed as,

\(\begin{array}{c}P\left( {X = 1} \right) = \frac{6}{{10}}\\ = 0.60\end{array}\)

Similarly, compute the probability\(P\left( {X = 2} \right)\). In this case, a pair consist of both board 1 and board 2.

The possible pair is\(\left\{ {\left( {1,2} \right)} \right\}\).

So, the probability is computed as,

\(\begin{aligned}P\left( {X = 2} \right) & = \frac{1}{{10}}\\ &= 0.10\end{aligned}\)

Therefore, the probability distribution of X is given as,

X

P(X)

0

0.30

1

0.60

2

0.10

04

Determine the cumulative distribution function of X.

c.

From the problem, the cdf\(F\left( {X = x} \right)\) can be defined as,

\(F\left( {X = x} \right) = P\left( {X \le x} \right)\)

First, compute\(F\left( 0 \right)\) using the above formula:

\(\begin{aligned}F\left( {X = 0} \right) &= P\left( {X \le 0} \right)\\ &= P\left( {X = 0} \right)\\ = 0.30\end{aligned}\)

Then, compute\(F\left( 1 \right)\) using the above formula:

\(\begin{aligned}F\left( {X = 1} \right) &= P\left( {X \le 1} \right)\\ &= P\left( {X = 0} \right) + P\left( {X = 1} \right)\\ &= 0.30 + 0.60\\ &= 0.90\end{aligned}\)

Finally compute\(F\left( 2 \right)\) using the above formula:

\(\begin{aligned}F\left( {X = 2} \right) &= P\left( {X \le 2} \right)\\ &= P\left( {X = 0} \right) + P\left( {X = 1} \right) + P\left( {X = 2} \right)\\ &= 0.30 + 0.60 + 0.10\\ &= 1\end{aligned}\)

Therefore, the cumulative distribution functionof X is given as,

\(F\left( x \right) = \left\{ \begin{array}{l}0,\,\,\,\,\,\,\,\,\,\,{\rm{when}}\,x < 0\\0.3\,\,\,\,\,\,\,\,{\rm{when}}\,0 \le x < 1\\0.9\,\,\,\,\,\,\,\,{\rm{when}}\,1 \le x \le 2\\0.1\,\,\,\,\,\,\,\,\,{\rm{when}}\,x \ge 2\end{array} \right.\)

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

There are two Certified Public Accountants in a particular office who prepare tax returns for clients. Suppose that for a particular type of complex form, the number of errors made by the first preparer has a Poisson distribution with mean value \({{\rm{\mu }}_{\rm{1}}}\), the number of errors made by the second preparer has a Poisson distribution with mean value \({{\rm{\mu }}_{\rm{2}}}\), and that each CPA prepares the same number of forms of this type. Then if a form of this type is randomly selected, the function

\({\rm{p(x;}}{{\rm{\mu }}_{\rm{1}}}{\rm{,}}{{\rm{\mu }}_{\rm{2}}}{\rm{) = }}{\rm{.5}}\frac{{{{\rm{e}}^{{\rm{ - }}{{\rm{\mu }}_{\rm{1}}}}}{\rm{\mu }}_{\rm{1}}^{\rm{x}}}}{{{\rm{x!}}}}{\rm{ + }}{\rm{.5}}\frac{{{{\rm{e}}^{{\rm{ - }}{{\rm{\mu }}_{\rm{2}}}}}{\rm{\mu }}_{\rm{2}}^{\rm{x}}}}{{{\rm{x!}}}}{\rm{ x = 0,1,2,}}...\)

gives the \({\rm{pmf}}\) of \({\rm{X = }}\)the number of errors on the selected form.

a. Verify that \({\rm{p(x;}}{{\rm{\mu }}_{\rm{1}}}{\rm{,}}{{\rm{\mu }}_{\rm{2}}}{\rm{)}}\) is in fact a legitimate \({\rm{pmf}}\) (\( \ge {\rm{0}}\) and sums to \({\rm{1}}\)).

b. What is the expected number of errors on the selected form?

c. What is the variance of the number of errors on the selected form?

d. How does the \({\rm{pmf}}\) change if the first CPA prepares \({\rm{60\% }}\) of all such forms and the second prepares \({\rm{40\% }}\)?

Ageologist has collected 10 specimens of basaltic rock and \({\rm{10 }}\) specimens of granite. The geologist instructs a laboratory assistant to randomly select \({\rm{15}}\) of the specimens for analysis.

a. What is the \({\rm{pmf}}\)of the number of granite specimens selected for analysis?

b. What is the probability that all specimens of one of the two types of rock are selected for analysis?

c. What is the probability that the number of granite specimens selected for analysis is within \({\rm{1}}\)standard deviation of its mean value?

Let X = the number of nonzero digits in a randomly selected 4-digit PIN that has no restriction on the digits. What are the possible values of X? Give three possible outcomes and their associated X values.

a. For fixed n, are there values of p(\({\rm{0}} \le {\rm{p}} \le {\rm{1}}\)) for which V(X) \({\rm{ = 0}}\)? Explain why this is so? b. For what value of p is V(X) maximized? (Hint: Either graph V(X) as a function of p or else take a derivative.)

If the sample space S is an infinite set, does this necessarily imply that any rv X defined from S will have an infinite set of possible values? If yes, say why. If no, give an example.

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.