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Suppose small aircraft arrive at a certain airport according to a Poisson process with rate\(\alpha = 8\)per hour, so that the number of arrivals during a time period of t hours is a Poisson rv with parameter\(\mu = 8t\). a. What is the probability that exactly 6 small aircraft arrive during a one-hour period? At least\(6\)? At least\({\bf{10}}\)? b. What are the expected value and standard deviations of the number of small aircraft that arrive during a\({\bf{90}}\)-min period? c. What is the probability that at least\({\bf{20}}\)small aircraft arrive during a\({\bf{2}}.{\bf{5}}\)-hour period? That at most\({\bf{10}}\)arrive during this period?

Short Answer

Expert verified

\(\begin{array}{l}(a)\;P(X = 6) = 0.1221,\;P(X \ge 6) = 0.8088\;and\;P(X \ge 10) = 0.2834\\(b)\;Expectedvalue:12\\\;\;\;\;Standarddeviation:\sqrt {12} = 2\sqrt 3 \approx 3.4641\\(c)\;P(X \ge 20) = 0.5297\;and\;P(X \le 10) = 0.0108\end{array}\)

Step by step solution

01

Definition of Probability

The mathematical tool of probability is used to examine unpredictability. It is concerned with the possibility (probability) of an event occurring. If you throw a fair coin four times, the results are unlikely to be two heads and two tails.

02

Calculation for the determination of probability in part a.

Given:

\(\lambda = \mu = 8t\)

Formula Poisson probability:

\(P(X = k) = \frac{{{\lambda ^k}{e^{ - \lambda }}}}{{k!}}\)

(a)

\(t = 1\)

\(\lambda = \mu = 8t = 8(1) = 8\)

Evaluate the formula at\(k = 0,1,2, \ldots ,10\):

\(\begin{array}{l}P(X = 0) = \frac{{{8^0}{e^{ - 8}}}}{{0!}} \approx 3.3546 \times {10^{ - 4}}\\P(X = 1) = \frac{{{8^1}{e^{ - 8}}}}{{1!}} \approx 0.0027\\P(X = 5) = \frac{{{8^5}{e^{ - 8}}}}{{5!}} \approx 0.0916\\P(X = 6) = \frac{{{8^6}{e^{ - 8}}}}{{6!}} \approx 0.1221\\.\\.\\.\\P(X = 9) = \frac{{{8^9}{e^{ - 8}}}}{{9!}} \approx 0.1241\end{array}\)

03

Calculation for the determination of probability in part a.

Addition rule for disjoint or mutually exclusive events:

\(P(A{\rm{ or }}B) = P(A) + P(B)\)

Add the corresponding probabilities:

\(\begin{array}{l}P(X \ge 6) = 1 - P(X < 6) = 1 - P(X = 0) - P(X = 1) - \ldots - P(X = 5)\\\;\;\;\;\;\;\;\;\;\;\;\; = 1 - 3.3546 \times {10^{ - 4}} + 0.0027 + \ldots + 0.0916\\\;\;\;\;\;\;\;\;\;\;\;\; = 0.8088\end{array}\)

Command \(TI83/84\)-calculator: \(1\)-Poissoncdf\((8,5)\)

\(\begin{array}{l}P(X \le 10) = 1 - P(X < 10) = 1 - P(X = 0) - P(X = 1) - \ldots - P(X = 9)\\\;\;\;\;\;\;\;\;\;\;\;\;\;\; = 1 - 3.3546 \times {10^{ - 4}} - 0.0027 - \ldots - 0.1241\\\;\;\;\;\;\;\;\;\;\;\;\;\;\; = 0.2834\end{array}\)

Command \(TI83/84\)-calculator: \(1\) -Poissoncdf\((8,9)\)

04

Calculation for the determination of standard deviation in part b.

(b)

\(t = 90\;{\rm{min}} = 1.5{\rm{ hours }}\)

The mean (expected value) is the product of the rate per hour and the number of hours:

\(\lambda = \mu = 8t = 8(1.5) = 12\)

The standard deviation of a Poisson distribution is the square root of the mean:

\(\sigma = \sqrt \mu = \sqrt \lambda = \sqrt {12} = 2\sqrt 3 \approx 3.4641\)

05

Calculation for the determination of probability in part c.

(c)

\(\begin{array}{l}t = 2.5\\\lambda = \mu = 8\\t = 8(2.5) = 20\end{array}\)

Evaluate the formula at\(k = 0,1,2, \ldots ,19\):

\(\begin{array}{l}P(X = 0) = \frac{{{{20}^0}{e^{ - 20}}}}{{0!}} \approx 2.0612 \times {10^{ - 9}}\\P(X = 1) = \frac{{{{20}^1}{e^{ - 20}}}}{{1!}} \approx 4.1223 \times {10^{ - 8}} \cdots \\P(X = 10) = \frac{{{{20}^{10}}{e^{ - 20}}}}{{10!}} \approx 0.0058\\P(X = 19) = \frac{{{{20}^{19}}{e^{ - 20}}}}{{19!}} \approx 0.0888\end{array}\)

Addition rule for disjoint or mutually exclusive events:

\(P(A{\rm{ or }}B) = P(A) + P(B)\)

06

Calculation for the determination of probability in part c.

Add the corresponding probabilities:

\(\begin{array}{l}P(X \le 19) = P(X = 0) + P(X = 1) + \ldots + P(X = 19)\\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, = 2.0612 \times {10^{ - 9}} + 4.1223 \times {10^{ - 8}} + \ldots + 0.0888\\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, = 0.4703\end{array}\)

Command \(TI83/84\)-calculator: Poissoncdf\((20,19)\)

\(\begin{array}{l}P(X \le 10) = P(X = 0) + P(X = 1) + \ldots + P(X = 10)\\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, = 2.0612 \times {10^{ - 9}} + 4.1223 \times {10^{ - 8}} + \ldots + 0.0058\\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, = 0.0108\end{array}\)

Command \(TI83/84\)-calculator: Poissoncdf\((20,10)\)

Complement rule:

\(P({\mathop{\rm not}\nolimits} A) = 1 - P(A)\)

Use the complement rule:

\(\begin{array}{l}P(X \ge 20) = 1 - P(X < 20)\\\;\;\;\;\;\;\;\;\;\;\;\;\;\,\, = 1 - P(X \le 19)\\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, = 1 - 0.4703\\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, = 0.5297\end{array}\)

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