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This gives us the following theorem:

Binomial probability theorem

The probability of obtaining k size 12{k} {} successes in n size 12{n} {} independent Bernoulli trials is given by

P n , k ; p = nCkp k q n k size 12{P left (n,k;p right )= ital "nCkp" rSup { size 8{k} } q rSup { size 8{n - k} } } {}

where p size 12{p} {} denotes the probability of success and q = 1 p size 12{q= left (1 - p right )} {} the probability of failure.

We use the above formula to solve the following examples.

If a coin is flipped 10 times, what is the probability that it will fall heads 3 times?

Let S size 12{S} {} denote the probability of obtaining a head, and F the probability of obtaining a tail.

Clearly, n = 10 size 12{n="10"} {} , k = 3 size 12{k=3} {} , p = 1 / 2 size 12{p=1/2} {} , and q = 1 / 2 size 12{q=1/2} {} .

Therefore,

b 10 , 3 ; 1 / 2 = 10 C3 1 / 2 3 1 / 2 7 = . 1172 size 12{b left ("10",3;1/2 right )="10"C3 left (1/2 right ) rSup { size 8{3} } left (1/2 right ) rSup { size 8{7} } = "." "1172"} {}
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If a basketball player makes 3 out of every 4 free throws, what is the probability that he will make 6 out of 10 free throws in a game?

The probability of making a free throw is 3 / 4 size 12{3/4} {} . Therefore, p = 3 / 4 size 12{p=3/4} {} , q = 1 / 4 size 12{q=1/4} {} , n = 10 size 12{n="10"} {} , and k = 6 size 12{k=6} {} .

Therefore,

b 10 , 6 ; 3 / 4 = 10 C6 3 / 4 6 1 / 4 4 = . 1460 size 12{b left ("10",6;3/4 right )="10"C6 left (3/4 right ) rSup { size 8{6} } left (1/4 right ) rSup { size 8{4} } = "." "1460"} {}
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If a medicine cures 80% of the people who take it, what is the probability that of the eight people who take the medicine, 5 will be cured?

Here p = . 80 size 12{p= "." "80"} {} , q = . 20 size 12{q= "." "20"} {} , n = 8 size 12{n=8} {} , and k = 5 size 12{k=5} {} .

b 8,5 ; . 80 = 8C5 . 80 5 . 20 3 = . 1468 size 12{b left (8,5; "." "80" right )=8C5 left ( "." "80" right ) rSup { size 8{5} } left ( "." "20" right ) rSup { size 8{3} } = "." "1468"} {}
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If a microchip manufacturer claims that only 4% of his chips are defective, what is the probability that among the 60 chips chosen, exactly three are defective?

If S size 12{S} {} denotes the probability that the chip is defective, and F size 12{F} {} the probability that the chip is not defective, then p = . 04 size 12{p= "." "04"} {} , q = . 96 size 12{q= "." "96"} {} , n = 60 size 12{n="60"} {} , and k = 3 size 12{k=3} {} .

b 60 , 3 ; . 04 = 60 C3 . 04 3 . 96 57 = . 2138 size 12{b left ("60",3; "." "04" right )="60"C3 left ( "." "04" right ) rSup { size 8{3} } left ( "." "96" right ) rSup { size 8{"57"} } = "." "2138"} {}
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If a telemarketing executive has determined that 15% of the people contacted will purchase the product, what is the probability that among the 12 people who are contacted, 2 will buy the product?

If S denoted the probability that a person will buy the product, and F the probability that the person will not buy the product, then p = . 15 size 12{p= "." "15"} {} , q = . 85 size 12{q= "." "85"} {} , n = 12 size 12{n="12"} {} , and k = 2 size 12{k=2} {} .

b 12 , 2, . 15 = 12 C2 . 15 2 . 85 10 = . 2924 size 12{b left ("12",2, "." "15" right )="12"C2 left ( "." "15" right ) rSup { size 8{2} } left ( "." "85" right ) rSup { size 8{"10"} } = "." "2924"} {} .

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Bayes' formula

In this section, we will develop and use Bayes' Formula to solve an important type of probability problem. Bayes' formula is a method of calculating the conditional probability P F E size 12{P left (F \lline E right )} {} from P E F size 12{P left (E \lline F right )} {} . The ideas involved here are not new, and most of these problems can be solved using a tree diagram. However, Bayes' formula does provide us with a tool with which we can solve these problems without a tree diagram.

We begin with an example.

Suppose you are given two jars. Jar I contains one black and 4 white marbles, and Jar II contains 4 black and 6 white marbles. If a jar is selected at random and a marble is chosen,

  1. What is the probability that the marble chosen is a black marble?
  2. If the chosen marble is black, what is the probability that it came from Jar I?
  3. If the chosen marble is black, what is the probability that it came from Jar II?

Let J I size 12{J`I} {} I be the event that Jar I is chosen, J II size 12{J ital "II"} {} be the event that Jar II is chosen, B size 12{B} {} be the event that a black marble is chosen and W size 12{W} {} the event that a white marble is chosen.

We illustrate using a tree diagram.

The figure shows that there are 2 available jars with marbles in them to choose from. The Tree diagram shows the probability of choosing either jar, while also giving the probability of choosing a white or black marble from either.

  1. The probability that a black marble is chosen is P B = 1 / 10 + 2 / 10 = 3 / 10 size 12{P left (B right )=1/"10"+2/"10"=3/"10"} {} .

  2. To find P J I B size 12{P left (J`I \lline B right )} {} , we use the definition of conditional probability, and we get

    P J I B = P J I B P B = 1 / 10 3 / 10 = 1 3 size 12{P left (J`I \lline B right )= { {P left (J`I intersection B right )} over {P left (B right )} } = { {1/"10"} over {3/"10"} } = { {1} over {3} } } {}
  3. Similarly, P J II B = P J II B P B = 2 / 10 3 / 10 = 2 3 size 12{P left (J` ital "II" \lline B right )= { {P left (J` ital "II" intersection B right )} over {P left (B right )} } = { {2/"10"} over {3/"10"} } = { {2} over {3} } } {}

    In parts b and c, the reader should note that the denominator is the sum of all probabilities of all branches of the tree that produce a black marble, while the numerator is the branch that is associated with the particular jar in question.

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Source:  OpenStax, Applied finite mathematics. OpenStax CNX. Jul 16, 2011 Download for free at http://cnx.org/content/col10613/1.5
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