Difference between revisions of "SOCR EduMaterials Activities Discrete Probability examples"

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* '''Description''':  You can access the applets for the distributions at  http://www.socr.ucla.edu/htmls/SOCR_Distributions.html .
+
== [[SOCR_EduMaterials_DistributionsActivities |SOCR Distribution Activities]] - Discrete Probability Distribution Activity ==
−
* '''Example 1:'''
 
−
Find the probability that 3 out of 8 plants will survive a frost, given that any such plant will survive a frost with probability of 0.30. Also, find the probability that at least 1 out of 8 will survive a frost. What is the expected value and standard deviation of the number of plants that survive the frost?
 
−
* '''Answer:'''
 
−
*<math> X \sim b(8,0.3) </math>, <math> P(X=3)= {8 \choose 3} 0.3^30.7^5=0.2541</math>
 
−
*<math> P(X \ge 1)=1-P(X=0)=1-.7^8=0.942</math>
 
−
*<math> E(X) = np = 8 \times 0.3=2.4 </math>
 
−
*<math> Sd(X)= \sqrt{npq}=\sqrt{8\times 0.30 \times 0.70}=1.3</math>
 
  
−
Below you can see a SOCR snapshot for this example:
+
===Description===
 +
You can access the applets for the distributions at  http://www.socr.ucla.edu/htmls/SOCR_Distributions.html .
 +
===Example 1===
 +
:: Find the probability that 3 out of 8 plants will survive a frost, given that any such plant will survive a frost with probability of 0.30. Also, find the probability that at least 1 out of 8 will survive a frost. What is the expected value and standard deviation of the number of plants that survive the frost?
 +
'''Solution'''
 +
::<math> X \sim b(8,0.3) </math>, <math> P(X=3)= {8 \choose 3} 0.3^30.7^5=0.2541</math>
 +
::Below you can see SOCR a snapshot for this example:
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example1.jpg|600px]]</center>
 +
::<math> P(X \ge 1)=1-P(X=0)=1-.7^8=0.942</math>
 +
::Below you can see SOCR a snapshotfor this example:
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example1_2nd.jpg|600px]]</center>
 +
::<math> E(X) = np = 8 \times 0.3=2.4 </math>
 +
::<math> Sd(X)= \sqrt{npq}=\sqrt{8\times 0.30 \times 0.70}=1.3</math>
  
−
<center>[[Image: SOCR_Activities_Binomial_Christou_example1.jpg|600px]]</center>
 
  
 +
===Example 2===
 +
::If the probabilities of having a male or female offspring are both 0.50, find the probability that a family’s fifth child is their first son.
 +
'''Solution'''
 +
::<math> X \sim geometric(0.5)</math>, <math>P(X=5)= (.5)^4 \times .5=0.03125</math>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example2.jpg|600px]]</center>
  
−
* '''Example 2:'''
+
===Example 3===
−
If the probabilities of having a male or female offspring are both 0.50, find the probability that a familiy's fifth child is their first son.
+
::A complex electronic system is built with a certain number of backup components in its subsystem. One subsystem has 4 identical components, each with probability of 0.20 of failing in less than 1000 hours. The subsystem will operate if at least 2 of the 4 components are operating. Assume the components operate independently.  
−
* '''Answer:'''
+
::a.''' Find the probability that exactly 2 of the 4 components last longer than 1000 hours.
−
*<math>P(X=5)= 0.50^5=0.03125</math>
+
::b.''' Find the probability that the subsystem operates longer than 1000 hours.
−
* '''Example 3:'''
 
−
**a. <math>X \sim b(4,0.8) </math>, <math> P(X=2)= {4 \choose 2} 0.8^2 0.2^2=0.1536</math>
 
−
**b. <math>P(X\ge 2)= {4 \choose 2} 0.8^2 0.2^2+{4 \choose 3} 0.8^3 0.2^1+{4 \choose 4} 0.8^4=0.9728</math>
 
−
* '''Example 4:'''
 
−
* <math>P(X=5)=0.7^4 0.3=0.07203,</math>where X represents the number of trials.
 
−
* '''Example 5:'''
 
−
<math> E(X)=\frac{1}{p}=\frac{1}{0.30}=3.33</math>
 
  
−
* '''Example 6:'''
+
'''Solution'''
−
**a. <math>X \sim b(5,0.90). P(X=4)= {5 \choose 4} 0.9^4 0.1^1=0.32805</math>
+
::a.''' <math>X \sim b(4,0.8) </math>, <math> P(X=2)= {4 \choose 2} 0.8^2 0.2^2=0.1536</math>
−
**<math>P(X\ge 1)= 1-P(X=0)= 1- 0.1^4=0.9999</math>
+
::<center>[[Image: SOCR_Activities_Binomial_Christou_example3.jpg|600px]]</center>
−
**b. P(X=0)=.001,
+
::b.''' <math>P(X\ge 2)= {4 \choose 2} 0.8^2 0.2^2+{4 \choose 3} 0.8^3 0.2^1+{4 \choose 4} 0.8^4=0.9728</math>
−
0.001= 0.1^n
+
::<center>[[Image: SOCR_Activities_Binomial_Christou_example3_2nd.jpg|600px]]</center>
−
n= 3
+
 
−
* '''Example 7:'''
+
===Example 4===
 +
:::Suppose that 30% of the applicants for a certain industrial job have advanced training in computer programming. Applicants are interviewed sequentially and are selected at random from the pool. Find the probability that the first applicant having advanced raining in computer programming is found on the fifth interview.
 +
'''Solution'''
 +
:: <math> X \sim geometric(0.3) </math>;<math>P(X=5)=0.7^4 \times 0.3=0.07203</math> where X represents the number of trials.
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example4.jpg|600px]]</center>
 +
 
 +
===Example 5===
 +
::Refer to Example 4. What is the expected number of applicants who need to be interviewed in order to find the first one with advanced training in computer programming?
 +
'''Solution'''
 +
::<math> E(X)=\frac{1}{p}=\frac{1}{0.30}=3.33</math>
 +
 
 +
===Example 6===
 +
::A missile protection system consists of n radar sets operating independently, each with probability 0.90  of detecting a missile entering a zone.
 +
::a.''' If n= and a missile enters the zone what is the probability that exactly 4 radar sets detect the missile? At least one?
 +
::b.''' How large must n be if we require the probability of detecting a missile to be 0.999?
 +
 
 +
'''Solution'''
 +
::a.''' <math>X \sim b(5,0.90). P(X=4)= {5 \choose 4} 0.9^4 0.1^1=0.32805</math>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example6_1st.jpg|600px]]</center>
 +
::<math>P(X\ge 1)= 1-P(X=0)= 1- 0.1^4=0.9999</math>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example6_2nd.jpg|600px]]</center>
 +
::b.''' <math>P(X=0)=.001, 0.001= 0.1^n </math> Thus <math>n=3</math>
 +
::In the first snapshot below, where<math>n=2, P(X\ge1)=0.99,</math> which is too small. In the second snapshot, we can see that when n is increased to 3, <math>P(X\ge1)</math> increases to nearly 0.999.
 +
::<center>n=2</center>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example6_b_n=2.jpg|600px]]</center>
 +
::<center>n=3</center>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example6_b_n=3.jpg|600px]]</center>
 +
 
 +
===Example 7===
 +
::Construct a probability histogram for the binomial probability distribution for each of the following: n=5,p=0.1, n=5,p=0.5, n=5,p=0.9. What do you observe? Explain.
 +
'''Solution'''
 +
::We observe that if p=0.5 the distribution resembles the normal distribution, with mean <math>np=0.25</math>. Values above and below the mean are distributed symmetrically around the mean. ::Also, the probability histograms for p=0.1 and p=0.9 are mirror images of each other.
 +
::<center>n=5,p=0.1</center>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example7_p=1.jpg|600px]]</center>
 +
::<center>n=5,p=0.5</center>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example7_b_n=5.jpg|600px]]</center>
 +
::<center>n=5,p=0.9</center>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example7_b_n=9.jpg|600px]]</center>
 +
 
 +
===Example 8===
 +
::On a population of consumers, 60% prefer a certain brand of ice cream. If consumers are randomly selected,
 +
::a.''' what is the probability that exactly 3 people have to be interviewed to encounter the first consumer who prefers this brand of ice cream?
 +
::b.''' what is the probability that at least 3 people have to be interviewed to encounter the first consumer who prefers this brand of ice cream?
 +
 
 +
'''Solution'''
 +
::a.''' <math> X \sim geometric(0.6);</math><math>P(X=3)=0.4 \times 0.4 \times 0.6=0.096</math><center>[[Image: SOCR_Activities_Binomial_Christou_example8_a.jpg|600px]]</center>
 +
::b.''' <math>P(X \ge3)=1-P(X=1)-P(X=2)=1-(0.60+0.40 \times .60) = 0.16</math>
 +
<center>[[Image: SOCR_Activities_Binomial_Christou_example8_b.jpg|600px]]</center>
 +
 
 +
===Example 9===
 +
::The alpha marketing research company employs consumer panels to explore preferences for new products. The current inquiry involves a taste test comparison between a standard brand A vanilla ice cream and a new one of reduced sugar. The company recruits panels of five consumers at a time and determines how many of the five prefer the new product. Their objective is to obtain a panel of five in which all five consumers prefer the new product. The actual probability that an individual will prefer the new product is 0.40.
 +
::a.''' What is the probability that all five consumers will prefer the new product?
 +
::b.''' What is the exact probability that alpha will go through 60 panels (each of five people) without finding a single panel of five which unanimously prefer the new product?
 +
 
 +
'''Solution'''
 +
::a.''' <math> X \sim b(5,0.4) </math>; <math> P(X=5)= {5 \choose 5} 0.4^5 \times 0.6^0=0.01024</math>
 +
::<center>[[Image:SOCR_Activities_Binomial_Christou_example9_a.jpg|600px]]</center>
 +
::b.''' In this part we will look at every group of 5 people as one unit. We will denote success as the event that all 5 people in a group prefer the new product, and failure as the event that at least one person in a group does not prefer the new product. Therefore, <math>p=0.01024</math>. So,
 +
<math> X \sim geometric(0.01024)</math>;P(X=60)= (1-.01024)^[60] = 53.9%</math>
 +
::Below you can see a SOCR snapshot for this example:
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example9_b.jpg|600px]]</center>
 +
===Example 10===
 +
::The Southland produce uses the following scheme to assign a quality ranking to incoming shipments of peaches.
 +
::Select four peaches at random.
 +
:::If all four peaches are unbruised, then the shipment is classified A.
 +
:::If three of the four peaches are unbruised, then select an additional four peaches.
 +
:::If all of these additional four peaches are unbruised, then the shipment is classified A.
 +
:::If two or more of these additional four peaches are unbruised, then the shipment is classified B.
 +
:::If zero or one of these additional four peaches are unbruised, then the shipment is classified C.
 +
:::If two or fewer of the four peaches are unbruised, then the shipment is classified C.
 +
 
 +
::a.''' If the proportion of unbruised peaches in a shipment is 0.90, find the probability that the shipment will be classified A. Assume the shipment is very large so the probability of selecting an unbruised peach practically remains constant.
 +
::b.''' What is the probability that the shipment will be classified C? Same assumption as in part (a).
 +
 
 +
 
 +
'''Solution'''
 +
::a.''' We will denote the number of unbruised peaches in our first selection X, and the number of unbruised peaches in our second selection Y. <math>P(shipment=A)=</math>P(all four peaches are unbruised)+P(three of the peaches are unbruised) X P(four additional peaches are unbruised)= <math>P(X=4)+P(X=3)\times P(Y=4).</math>
 +
::<math> X \sim b(4,0.9) </math>, <math> P(X=4)= {4 \choose 4} 0.9^4 0.1^0= 0.6561</math>
 +
::Here is the snapshot in SOCR:
 +
 
 +
::<center>[[Image:SOCR_Activities_Binomial_Christou_example10_first.jpg|600px]]</center>
 +
::<math> Y \sim b(4,0.9) </math>, <math> P(Y=3)= {4 \choose 3} 0.9^3 0.1^1= 0.2916</math>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example10_second.jpg|600px]]</center>
 +
::<math> Y \sim b(4,0.9) </math>, <math> P(Y=4)= {4 \choose 4} 0.9^4 0.1^0= 0.6561</math>
 +
::Therefore, <math>P(shipment=A)=0.6561+ (0.2916)(0.6561)=0.8474</math>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example10_third.jpg|600px]]</center>
 +
 
 +
::b.'''<math>P(Shipment=C)=</math>P(three of the first four peaches are unbruised) X P(zero or one of the additional four peaches are unbruised) +P(two or fewer of the first four peaches are unbruised). The first selection of peaches = X. The second selection=Y.
 +
::<math> X \sim b(4,0.9) </math>, <math> P(X=3)= {4 \choose 3} 0.9^3 0.1^1= 0.2916</math>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example10_b_first.jpg|600px]]</center>
 +
::<math> Y \sim b(4,0.9) </math>, <math> P(Y=0)= {4 \choose 0} 0.9^0 0.1^4= 0.0001</math>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example10_b_second.jpg|600px]]</center>
 +
::<math>P(Y=1)={4 \choose 1} 0.9^1 0.1^3=0.0036</math>
 +
::<center>[[Image: SOCR_Activities_Binomial_Christou_example10_b_third.jpg|600px]]</center>
 +
::Therefore <math>P(Y=0 or 1) = 0.0001+.0009=0.001.</math>
 +
::<math>P(X\le2)=P(X=0)+P(X=1)+P(X=2)= {4 \choose 0} 0.9^0 0.1^4 + {4 \choose 1} 0.9^1 0.1^3+{4 \choose 2} 0.9^2 0.1^2= 0.0523</math>
 +
::Therefore P(shipment=C)=<math>(0.2916 \times 0.001)+.0523 = 0.052</math>
 +
 
 +
===Example 11===
 +
 
 +
::A communication system consists of n components, each of which will, independently, function with probability 0.40. The total system will be able to operate effectively if at least one-half of its components function.
 +
::a.''' Would you choose a communication system that consists of 5 components or one that consists of 3 components?
 +
::b.''' Suppose that a complex communication system consists of 200 components. What is the mean and standard deviation of the number of components that will function?
 +
 
 +
'''Solution'''
 +
::a.''' We want our system to function, so we would prefer a system with the highest probability of operating. A system will operate if at least half of its components function.
 +
::If n=3, P(functioning when n=3)=<math>P(X\ge 2). </math>
 +
<math>X \sim b(3,0.40). P(X \ge2)= P(X=2)+P(X=3)= {3 \choose 2} 0.4^2 0.6^1+{3 \choose 3} 0.4^3 0.6^0= 0.352</math>
 +
<center>[[Image:SOCR_Activities_Binomial_Christou_example11_n=3.jpg|600px]]
 +
</center>
 +
::If n=5, P(functioning when n=5)=<math>P(X\ge 3). </math>
 +
<math>X \sim b(5,0.40). P(X \ge3)= P(X=3)+P(X=4)+P(X=5)= {5 \choose 3} 0.4^3 0.6^2+{5 \choose 4} 0.4^4 0.6^1+{5 \choose 5} 0.4^5 0.6^0=0.31744</math>
 +
<center>[[Image:SOCR_Activities_Binomial_Christou_example11_n=5.jpg|600px]]
 +
</center>
 +
::Therefore, it is better to have 3 components, because we will have a better chance of having a system that operates.
 +
::b.''' Again, <math>X \sim b(200,0.40).</math> mean=expected value = <math>np=200 \times 0.4 = 80; SD=\sqrt{npq}=\sqrt{200 \times 0.4 \times 0.6}=6.92</math>
 +
<center>[[Image:SOCR_Activities_Binomial_Christou_example11_b.jpg|600px]]
 +
</center>
 +
 
 +
<hr>
 +
* [[SOCR_Videos_Distributions | SOCR Distribution Video Tutorial]]
 +
* [[About_pages_for_SOCR_Distributions | More about SOCR Distributions]]
 +
* [[Help_pages_for_SOCR_Distributions | SOCR Distributions Help]]
 +
* SOCR Home page: http://www.socr.ucla.edu
 +
 
 +
{{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_EduMaterials_Activities_Discrete_Probability_examples}}

Latest revision as of 23:29, 10 December 2008

SOCR Distribution Activities - Discrete Probability Distribution Activity

Description

You can access the applets for the distributions at http://www.socr.ucla.edu/htmls/SOCR_Distributions.html .

Example 1

Find the probability that 3 out of 8 plants will survive a frost, given that any such plant will survive a frost with probability of 0.30. Also, find the probability that at least 1 out of 8 will survive a frost. What is the expected value and standard deviation of the number of plants that survive the frost?

Solution

\[ X \sim b(8,0.3) \], \( P(X=3)= {8 \choose 3} 0.3^30.7^5=0.2541\)
Below you can see SOCR a snapshot for this example:
SOCR Activities Binomial Christou example1.jpg
\[ P(X \ge 1)=1-P(X=0)=1-.7^8=0.942\]
Below you can see SOCR a snapshotfor this example:
SOCR Activities Binomial Christou example1 2nd.jpg
\[ E(X) = np = 8 \times 0.3=2.4 \]
\[ Sd(X)= \sqrt{npq}=\sqrt{8\times 0.30 \times 0.70}=1.3\]


Example 2

If the probabilities of having a male or female offspring are both 0.50, find the probability that a family’s fifth child is their first son.

Solution

\[ X \sim geometric(0.5)\], \(P(X=5)= (.5)^4 \times .5=0.03125\)
SOCR Activities Binomial Christou example2.jpg

Example 3

A complex electronic system is built with a certain number of backup components in its subsystem. One subsystem has 4 identical components, each with probability of 0.20 of failing in less than 1000 hours. The subsystem will operate if at least 2 of the 4 components are operating. Assume the components operate independently.
a. Find the probability that exactly 2 of the 4 components last longer than 1000 hours.
b. Find the probability that the subsystem operates longer than 1000 hours.

Solution

a. \(X \sim b(4,0.8) \), \( P(X=2)= {4 \choose 2} 0.8^2 0.2^2=0.1536\)
SOCR Activities Binomial Christou example3.jpg
b. \(P(X\ge 2)= {4 \choose 2} 0.8^2 0.2^2+{4 \choose 3} 0.8^3 0.2^1+{4 \choose 4} 0.8^4=0.9728\)
SOCR Activities Binomial Christou example3 2nd.jpg

Example 4

Suppose that 30% of the applicants for a certain industrial job have advanced training in computer programming. Applicants are interviewed sequentially and are selected at random from the pool. Find the probability that the first applicant having advanced raining in computer programming is found on the fifth interview.

Solution

\[ X \sim geometric(0.3) \];\(P(X=5)=0.7^4 \times 0.3=0.07203\) where X represents the number of trials.
SOCR Activities Binomial Christou example4.jpg

Example 5

Refer to Example 4. What is the expected number of applicants who need to be interviewed in order to find the first one with advanced training in computer programming?

Solution

\[ E(X)=\frac{1}{p}=\frac{1}{0.30}=3.33\]

Example 6

A missile protection system consists of n radar sets operating independently, each with probability 0.90 of detecting a missile entering a zone.
a. If n= and a missile enters the zone what is the probability that exactly 4 radar sets detect the missile? At least one?
b. How large must n be if we require the probability of detecting a missile to be 0.999?

Solution

a. \(X \sim b(5,0.90). P(X=4)= {5 \choose 4} 0.9^4 0.1^1=0.32805\)
SOCR Activities Binomial Christou example6 1st.jpg
\[P(X\ge 1)= 1-P(X=0)= 1- 0.1^4=0.9999\]
SOCR Activities Binomial Christou example6 2nd.jpg
b. \(P(X=0)=.001, 0.001= 0.1^n \) Thus \(n=3\)
In the first snapshot below, where\(n=2, P(X\ge1)=0.99,\) which is too small. In the second snapshot, we can see that when n is increased to 3, \(P(X\ge1)\) increases to nearly 0.999.
n=2
SOCR Activities Binomial Christou example6 b n=2.jpg
n=3
SOCR Activities Binomial Christou example6 b n=3.jpg

Example 7

Construct a probability histogram for the binomial probability distribution for each of the following: n=5,p=0.1, n=5,p=0.5, n=5,p=0.9. What do you observe? Explain.

Solution

We observe that if p=0.5 the distribution resembles the normal distribution, with mean \(np=0.25\). Values above and below the mean are distributed symmetrically around the mean. ::Also, the probability histograms for p=0.1 and p=0.9 are mirror images of each other.
n=5,p=0.1
SOCR Activities Binomial Christou example7 p=1.jpg
n=5,p=0.5
SOCR Activities Binomial Christou example7 b n=5.jpg
n=5,p=0.9
SOCR Activities Binomial Christou example7 b n=9.jpg

Example 8

On a population of consumers, 60% prefer a certain brand of ice cream. If consumers are randomly selected,
a. what is the probability that exactly 3 people have to be interviewed to encounter the first consumer who prefers this brand of ice cream?
b. what is the probability that at least 3 people have to be interviewed to encounter the first consumer who prefers this brand of ice cream?

Solution

a. \( X \sim geometric(0.6);\)\(P(X=3)=0.4 \times 0.4 \times 0.6=0.096\)
SOCR Activities Binomial Christou example8 a.jpg
b. \(P(X \ge3)=1-P(X=1)-P(X=2)=1-(0.60+0.40 \times .60) = 0.16\)
SOCR Activities Binomial Christou example8 b.jpg

Example 9

The alpha marketing research company employs consumer panels to explore preferences for new products. The current inquiry involves a taste test comparison between a standard brand A vanilla ice cream and a new one of reduced sugar. The company recruits panels of five consumers at a time and determines how many of the five prefer the new product. Their objective is to obtain a panel of five in which all five consumers prefer the new product. The actual probability that an individual will prefer the new product is 0.40.
a. What is the probability that all five consumers will prefer the new product?
b. What is the exact probability that alpha will go through 60 panels (each of five people) without finding a single panel of five which unanimously prefer the new product?

Solution

a. \( X \sim b(5,0.4) \); \( P(X=5)= {5 \choose 5} 0.4^5 \times 0.6^0=0.01024\)
SOCR Activities Binomial Christou example9 a.jpg
b. In this part we will look at every group of 5 people as one unit. We will denote success as the event that all 5 people in a group prefer the new product, and failure as the event that at least one person in a group does not prefer the new product. Therefore, \(p=0.01024\). So,

\( X \sim geometric(0.01024)\);P(X=60)= (1-.01024)^[60] = 53.9%</math>

Below you can see a SOCR snapshot for this example:
SOCR Activities Binomial Christou example9 b.jpg

Example 10

The Southland produce uses the following scheme to assign a quality ranking to incoming shipments of peaches.
Select four peaches at random.
If all four peaches are unbruised, then the shipment is classified A.
If three of the four peaches are unbruised, then select an additional four peaches.
If all of these additional four peaches are unbruised, then the shipment is classified A.
If two or more of these additional four peaches are unbruised, then the shipment is classified B.
If zero or one of these additional four peaches are unbruised, then the shipment is classified C.
If two or fewer of the four peaches are unbruised, then the shipment is classified C.
a. If the proportion of unbruised peaches in a shipment is 0.90, find the probability that the shipment will be classified A. Assume the shipment is very large so the probability of selecting an unbruised peach practically remains constant.
b. What is the probability that the shipment will be classified C? Same assumption as in part (a).


Solution

a. We will denote the number of unbruised peaches in our first selection X, and the number of unbruised peaches in our second selection Y. \(P(shipment=A)=\)P(all four peaches are unbruised)+P(three of the peaches are unbruised) X P(four additional peaches are unbruised)= \(P(X=4)+P(X=3)\times P(Y=4).\)
\[ X \sim b(4,0.9) \], \( P(X=4)= {4 \choose 4} 0.9^4 0.1^0= 0.6561\)
Here is the snapshot in SOCR:
SOCR Activities Binomial Christou example10 first.jpg
\[ Y \sim b(4,0.9) \], \( P(Y=3)= {4 \choose 3} 0.9^3 0.1^1= 0.2916\)
SOCR Activities Binomial Christou example10 second.jpg
\[ Y \sim b(4,0.9) \], \( P(Y=4)= {4 \choose 4} 0.9^4 0.1^0= 0.6561\)
Therefore, \(P(shipment=A)=0.6561+ (0.2916)(0.6561)=0.8474\)
SOCR Activities Binomial Christou example10 third.jpg
b.\(P(Shipment=C)=\)P(three of the first four peaches are unbruised) X P(zero or one of the additional four peaches are unbruised) +P(two or fewer of the first four peaches are unbruised). The first selection of peaches = X. The second selection=Y.
\[ X \sim b(4,0.9) \], \( P(X=3)= {4 \choose 3} 0.9^3 0.1^1= 0.2916\)
SOCR Activities Binomial Christou example10 b first.jpg
\[ Y \sim b(4,0.9) \], \( P(Y=0)= {4 \choose 0} 0.9^0 0.1^4= 0.0001\)
SOCR Activities Binomial Christou example10 b second.jpg
\[P(Y=1)={4 \choose 1} 0.9^1 0.1^3=0.0036\]
Error creating thumbnail: File missing
Therefore \(P(Y=0 or 1) = 0.0001+.0009=0.001.\)
\[P(X\le2)=P(X=0)+P(X=1)+P(X=2)= {4 \choose 0} 0.9^0 0.1^4 + {4 \choose 1} 0.9^1 0.1^3+{4 \choose 2} 0.9^2 0.1^2= 0.0523\]
Therefore P(shipment=C)=\((0.2916 \times 0.001)+.0523 = 0.052\)

Example 11

A communication system consists of n components, each of which will, independently, function with probability 0.40. The total system will be able to operate effectively if at least one-half of its components function.
a. Would you choose a communication system that consists of 5 components or one that consists of 3 components?
b. Suppose that a complex communication system consists of 200 components. What is the mean and standard deviation of the number of components that will function?

Solution

a. We want our system to function, so we would prefer a system with the highest probability of operating. A system will operate if at least half of its components function.
If n=3, P(functioning when n=3)=\(P(X\ge 2). \)

\(X \sim b(3,0.40). P(X \ge2)= P(X=2)+P(X=3)= {3 \choose 2} 0.4^2 0.6^1+{3 \choose 3} 0.4^3 0.6^0= 0.352\)

SOCR Activities Binomial Christou example11 n=3.jpg
If n=5, P(functioning when n=5)=\(P(X\ge 3). \)

\(X \sim b(5,0.40). P(X \ge3)= P(X=3)+P(X=4)+P(X=5)= {5 \choose 3} 0.4^3 0.6^2+{5 \choose 4} 0.4^4 0.6^1+{5 \choose 5} 0.4^5 0.6^0=0.31744\)

SOCR Activities Binomial Christou example11 n=5.jpg
Therefore, it is better to have 3 components, because we will have a better chance of having a system that operates.
b. Again, \(X \sim b(200,0.40).\) mean=expected value = \(np=200 \times 0.4 = 80; SD=\sqrt{npq}=\sqrt{200 \times 0.4 \times 0.6}=6.92\)
SOCR Activities Binomial Christou example11 b.jpg

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