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Section 3.6 A binomial distribution find the probability of r successes in n independent trials. Lets adjust the question a small bit. An independent trial is going to be repeated a few times. The probability of successes is p=0.4. Find the probability that the 2nd success happens on the 5th repitition of the trial. Title : Oct 9-9:40 AM (Page 1 of 6) Example: David is selling candy bars to raise money for a school trip. He is going house to house to sell the goodies. At each house there is a probability of 0.4 of selling one candy bar. What is the probability that David had to go to 8 houses in order to sell 5 candy bars? Title : Oct 9-9:44 AM (Page 2 of 6) Poisson Distribution: 1) The event is something counted in whole numbers. 2) The occurrences are independent. 3) The average frequency of occurrences for the time period (or per unit area) are known. 4) It is possible to count how many event have occured. **not posible(or reasonable) to count how many event have not occured. Title : Oct 9-9:53 AM (Page 3 of 6) Example: Suppose that you are working the phones for an office and the average number of phone calls you recieve per hour is 2. Compute the probability distribution of recieving x phone calls in a given hour. Title : Oct 9-9:56 AM (Page 4 of 6) Example: A utility company recors show trees fall on power lines on average of 3 times per week. What is the probability of a tree falling on a power line exactly once on a given day? What is the probability of a tree falling on a power line at least twice on a given day? Title : Oct 9-10:00 AM (Page 5 of 6) Example: The number of accidents in a month at a companies plants has been taulated and given in the table. n freq. 0 1 2 45 36 14 3 4 >= 5 1 0 4 Does the number of accidents meet a Poisson distribution? Title : Oct 9-10:02 AM (Page 6 of 6)