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# Chapter 7

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1. Chapter 7 Special Discrete Distributions

2. Binomial Distribution B(n,p) • Each trial results in one of two mutually exclusive outcomes. (success/failure) • There are a fixed number of trials • Outcomes of different trials are independent • The probability that a trial results in success is the same for all trials • The binomial random variable x is defined as the number of successes out of the fixed number

3. Are these binomial distributions? • Toss a coin 10 times and count the number of heads Yes • Deal 10 cards from a shuffled deck and count the number of red cards No, probability does not remain constant • Two parents with genes for O and A blood types and count the number of children with blood type O No, no fixed number

4. Toss a 3 coins and count the number of heads Find the discrete probability distribution X 0 1 2 3 P(x) .125 .375 .375 .125 Out of 3 coins that are tossed, what is the probability of getting exactly 2 heads?

5. Binomial Formula: Where:

6. Out of 3 coins that are tossed, what is the probability of getting exactly 2 heads?

7. The number of inaccurate gauges in a group of four is a binomial random variable. If the probability of a defect is 0.1, what is the probability that only 1 is defective? More than 1 is defective?

8. Binomialpdf(n,p,x) – this calculates the probability of a single binomial P(x = k) Binomialcdf(n,p,x) – this calculates the cumulative probabilities from P(0) to P(k) Calculator

9. A genetic trait of one family manifests itself in 25% of the offspring. If eight offspring are randomly selected, find the probability that the trait will appear in exactly three of them. At least 5?

10. In a certain county, 30% of the voters are Republicans. If ten voters are selected at random, find the probability that no more than six of them will be Republicans. P(x < 6) = binomcdf(10,.3,6) = .9894

11. Binomial formulas for mean and standard deviation

12. In a certain county, 30% of the voters are Republicans. How many Republicans would you expect in ten randomly selected voters? What is the standard deviation for this distribution?

13. Binomial Activity • In L1 – seq(x,x,0,10) • In L2 – binompdf(10, .1 ,L1) • Sketch histogram on board

14. Binomial Activity What happened to the shape of the distribution as the probability of success increased? As the probability of success increases, the shape changes from being skewed right to symmetrical at p =.5 to skewed left.

15. Binomial Activity • Calculate the mean and standard deviations for each of the probabilities • What do you notice? • As the probability of success increase, • the means increase. • the standard deviations increase to p = .5, then decrease. Their values are also symmetrical.

16. Geometric Distributions: • There are two mutually exclusive outcomes • Each trial is independent of the others • The probability of success remains constant for each trial. • The random variable x is the number of trials UNTIL the FIRST success occurs.

17. Differences between binomial & geometric distributions • The difference between binomial and geometric properties is that there is NOT a fixed number of trials in geometric distributions!

18. Other differences: • Binomial random variables start with 0 while geometric random variables start with 1 • Binomial distributions are finite, while geometric distributions are infinite

19. Geometric Formulas:

20. Count the number of boys in a family of four children. Binomial: X 0 1 2 3 4 Count children until first son is born Geometric: X 1 2 3 4 . . .

21. What is the probability that the first son is the fourth child born? What is the probability that the first son is born is at most the fourth child?

22. A real estate agent shows a house to prospective buyers. The probability that the house will be sold to the person is 35%. What is the probability that the agent will sell the house to the third person she shows it to? How many prospective buyers does she expect to show the house to before someone buys the house?

23. Geometric Activity • In L1 – input numbers 1-20 • In L2 – geometpdf(.1,L1) • Sketch • Find the means & standard deviations • What do you see?

24. Geometric Activity • Geometric distributions are skewed right and become more strongly skewed right as the probability of success increases • Mean & standard deviation of the distributions decrease as the probability of success increase

25. Poisson Distributions This distribution deals with the probabilities of rare events that occur infrequently in space, time, distance, area, etc. Examples: • The number of accidents that occur per month at a given intersection • The number of tardies per semester for a given student • The number of runs per inning in a baseball game

26. Properties: • The occurrence of a success in any interval is independent of that in any other interval • The probability that a success will occur in any interval is the same for all intervals of equal size and is proportional to the size of the interval • We observe a discretenumber of events in a continuous (fixed) interval.

27. Formulas: X = number of rare events per unit of time, space, etc. l = mean value of X (Greek letter lambda)

28. The number of accidents in an office building during a four-week period averages 2. What is the probability there will be one accident in the next four-week period? What is the probability that there will be more than two accidents in the next four-week period?

29. From 8:00 until 8:30 is a 30 minute period. From 8:00 until 9:00 is a 60 minute period. Since the period is doubled, you must double the mean amount of calls to keep it proportional! • The number of calls to a police department between 8 pm and 8:30 pm on Friday averages 3.5. • What is the probability of no calls during this period? • What is the probability of no calls between 8 pm and 9 pm on Friday night? • What is the mean and standard deviation of the number of calls between 10 pm and midnight on Friday night? P(X = 0) = poissonpdf(3.5,0) =.0302 Be sure to adjust l! P(X = 0) = poissonpdf(7,0) =.0009 m = 14 &s = 3.742

30. Examine the histograms of the Poisson distributions – l = 2 l = 4 What happens to the shape? What happens to the means? What happens to the standard deviations? l= 6

31. As l increases • The distributions become more symmetrical • The means increase • The standard deviations increase