1 / 19

Binomial Probability Distribution 1. The experiment must have a fixed number of trials .

Binomial Probability Distribution 1. The experiment must have a fixed number of trials . 2. The trials must be independent . (The outcome of any individual trial doesn’t affect the probabilities in the other trials.) 3. Each trial must have all outcomes classified into two categories .

Download Presentation

Binomial Probability Distribution 1. The experiment must have a fixed number of trials .

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Binomial Probability Distribution 1. The experiment must have a fixed number of trials. 2. The trials must be independent. (The outcome of any individual trial doesn’t affect the probabilities in the other trials.) 3. Each trial must have all outcomes classified into two categories. 4. The probabilities must remain constantfor each trial.

  2. Example:Construct a probability distribution table for the number of girls born if a couple has 4 children. This can also be done by using the TI – 83 / 84

  3. 1) use the formula P(x) = nCx• px•qn-x 2) UseTable A-1 in Appendix A 3) Use the TI – 83 / 84 There are three methods for calculating Binomial Probability Distributions

  4. Method 1 Binomial Probability Formula

  5. Method 1 Binomial Probability Formula n! • P(x) = • px• qn-x (n - x )! x!

  6. Method 1 Binomial Probability Formula n! • P(x) = • px• qn-x (n - x )! x! • P(x) = nCx• px•qn-x for calculators with nCr key, where r = x

  7. This is a binomial experiment where: n = 5 x = 3 p = 0.90 q = 0.10 Use method 1: Example: Find the probability of getting exactly 3 correct responses among 5 different requests from AT&T directory assistance. Assume in general, AT&T is correct 90% of the time.

  8. This is a binomial experiment where: n = 5 x = 3 p = 0.90 q = 0.10 Using the binomial probability formula to solve: P(3) = 5C3• 0.9 • 01 = 0.0.0729 Example: Find the probability of getting exactly 3 correct responses among 5 different requests from AT&T directory assistance. Assume in general, AT&T is correct 90% of the time. 2 3

  9. Method 2 Table A-1 in Appendix A P(x) n x 0 1 2 3 4 5 For n = 5 and p = 0.90 0.000 0.000 0.008 0.073 0.328 0.590 5 Table A-1

  10. Example (a): Find the probability of getting exactly 3 correct responses among 5 different requests from AT&T directory assistance. Assume in general, AT&T is correct 90% of the time. Using Table A-1 Use method 2:

  11. Example (b) : Find the probability of getting at least 3 correct responses among 5 different requests from AT&T directory assistance. Assume in general, AT&T is correct 90% of the time. Using Table A-1 Use method 2:

  12. Solution: a) P(3) = 0.073 b) P(at least 3) = P(3 or 4 or 5) = P(3) or P(4) or P(5) = 0.073 + 0.328 + 0.590 = 0.991 Method 2

  13. Example (a): Find the probability of getting exactly 3 correct responses among 5 different requests from AT&T directory assistance. Assume in general, AT&T is correct 90% of the time. Using your calculator Use method 3:

  14. Example (a): Find the probability of getting at least 3 correct responses among 5 different requests from AT&T directory assistance. Assume in general, AT&T is correct 90% of the time. Using your calculator Use method 3:

  15. Solution: A) binomialPDF(n,p,x) = 0.073 B) “ at least 3” means 3,4,5 so find the probability of 0, 1, 2 and subtract this from one. 1-BinomialCDF(n,p,x) = 0.991 Method 3

  16. µ = [x • P(x)] 2= [ x 2• P(x) ] - µ 2 MEAN, VARIANCE, STANDARD DEVIATIONFor Any Discrete Probability Distribution: = [ x 2• P(x) ] - µ 2

  17. µ = n • p 2 = n • p • q For Binomial Distributions ONLY: = n • p • q

  18. We previously discovered that this scenario could be considered a binomial experiment where: n = 14 p = 0.5 q = 0.5 Using the binomial distribution formulas: Example: Find the mean and standard deviation for the number of girls in groups of 14 births.

  19. We previously discovered that this scenario could be considered a binomial experiment where: n = 14 p = 0.5 q = 0.5 Using the binomial distribution formulas: µ = (14)(0.5) = 7 girls  = (14)(0.5)(0.5) = 1.9 girls (rounded) Example:Find the mean and standard deviation for the number of girls in groups of 14 births.

More Related