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Binomial Probability Distributions

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Title: Binomial Probability Distributions


1
Section 5-3
  • Binomial Probability Distributions

2
What does the prefix Bi mean?
  • We will now consider situations where there are
    exactly two outcomes
  • Yes/no to a survey question
  • Product is defective/not defective
  • Correct/Wrong response to a multiple choice
    question
  • Arrival time for an airline is on time/not on time

3
Conditions for a Binomial Probability Distribution
  • There are a fixed number of trials, n, that are
    identical and independent.
  • Each trial has exactly 2 outcomes success, S
    or failure, F
  • The probability of success must remain the same
    for each trial.

4
Notation
  • P(S) p
  • P(F) 1 p q
  • n of trials
  • x of successes
  • success is just what is being measured

5
Example 1
  • Determine whether the given procedure results in
    a binomial distribution.
  • Determining whether each of 3000 heart pacemakers
    is acceptable or defective.
  • Surveying people and asking them what they think
    of the current president.
  • Spinning the roulette wheel 12 times and finding
    the number of times that the outcome is an odd
    number.

6
Methods for finding binomial probabilities
  • Binomial Probability Formula
  • Table A-1, Appendix A
  • MINITAB

7
Example 2
A report from the Secretary of Health and Human
Services stated that 70 of single-vehicle
traffic fatalities that occur at night on
weekends involve an intoxicated driver. If a
sample of 10 single-vehicle traffic fatalities
that occur at night on a weekend is selected,
find the probability that exactly seven involve a
driver that is intoxicated.
  • This is a binomial experiment where
  • n 10 x 7 p 0.70 q 0.30

8
  • Using table generated in MINITAB

P(7) 0.266828
9
  • How about the probability of at least 8 involving
    an intoxicated driver?
  • P(at least 8) P(8) or P(9) or P(10)
  • 0.233474 0.121061 0.028248
  • 0.382783

10
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11
Example 3
  • In a clinical test of the drug Viagra, it was
    found that 4 of those in a placebo group
    experienced headaches.
  • Assuming that the same 4 rate applies to those
    taking Viagra, find the probability that among
    eight Viagra users, three experience headaches.

12
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