1. The number of monthly breakdowns of a computer is a random variable having a Poisson distribution with λ = 1.8. Use the formula for the Poisson distribution to find the probabilities that this computer will function a. without a breakdown; b. with only one breakdown.
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- Despite all efforts by the quality control department, the fabric made at benton corporation always contains a few defects. A certain type of fabric made at this corporation contains an average of 0.51 defects per 500 yards. Using the Poisson formula, find the probability that the number of defects in a given 500-yard piece of this fabric will be between two and four.P(between 2 and 4) =Determine if the following scenarios follow a Poisson distribution or do not follow a Poisson Distribution. • You work in a shoe shop and you want to find the distribution of the total number of people who come into the store in a day. You also observe that there are usually more people who come into the shop over lunchtime (10-2 pm) and more people who come into the store after they finish work (5 pm-6 pm). Let X be the number of people who come into the shoe shop on a given day. No - not Poisson • You love peanut butter and want to know how many people buy peanut butter from Trader Joe's. One summer you have nothing to do so you go and stand in Trader Joe's every day and count how many people buy peanut butter in a given week. You assume that consumers do not impact each other's decisions. Let Y be the number of people who buy peanut butter in a given week. Yes - Poisson You want to know how many people in a group of 100 take painkillers if they have a headache. You think that the…9. This is a simplified inventory problem. Suppose that it costs c dollars to stock anitem and that the item sells for s dollars. Suppose that the number of items thatwill be asked for by customers is a random variable with the frequency functionp(k). Find a rule for the number of items that should be stocked in order tomaximize the expected income. (Hint: Consider the difference of successiveterms.)
- Suppose that the number of traffic accident claims received in a month is modeled by Poisson distribution with intensity λ = 4. Assume that each traffic accident claim takes values $150, $300 or $450 equally likely. Calculate the probability that the total traffic accident claim amounts to exactly $1500.You and your friends have a large messaging group on GroupMe. The number of messages that are received in the group follows a Poisson distribution with an average of 30 per hour – call this random variable X. Let T be an exponentially distributed random variable that represents the time between messages received. 1. What is the probability that there are between 26 and 35 messages in the next hour? 2. What is the probability that there are exactly 30 messages in the next two hours? 3. What is the average for the variable, T?Part 1 of 6 Determine whether the following value is a continuous random variable, discrete random variable, or not a random variable. a. The number of light bulbs that burn out in the next year in a room with 13 bulbs b. The hair color of adults in the United States c. The number of pigeons in a country d. The time it takes for a light bulb to burn out e. The number of free-throw attempts before the first shot is missed f. The number of people in a restaurant that has a capacity of 150 ..... a. Is the number of light bulbs that burn out in the next year in a room with 13 bulbs a discrete random variable, continuous random variable, or not a O A. It is a discrete random variable. O B. It is a continuous random variable. O C. It is not a random variable.
- 1. The following table shows the probabilities associated with the discrete random variable, which counts the number of sales performed at a peak hour in a store in a downtown commercial. It is known that the probability that at most three sales is 40%, that at least five sales are made is 55%, but having less than 6 sales is 63%. one). Find the values of a, b, and c. two). Calculate the cumulative distribution function 3). Find the expectation and varianceQ.6. Use the binomial distribution in which n 6 and p = 0.3 to %3D calculate the following probabilities: (a). X is at most 1. (b). X is at least 2. (c). X is more than 5. (d). X is less than 6.1. Provide the graphs for PDF and CDF of the random variable B which takes on values of 1 and 0 with probability of 0.40 and 0.60. (Don't forget the horizontal axis must be sorted).
- The random variable x represents the number of emails a student receives on a day. Assume it has a Poisson distribution with a mean of 14.3 emails. Find the probability that in a random day the student receives 3 emails. Round your answer to four decimal places.The number of admissions per day at an emergency room has a Poisson distribution and its parameter is 5.Find the probability of I. At least 3 admissions per day II. At most 8 admissions per day.