(31) A baseball teams plays 182 games in a season and we are tracking their record over threeseasons. Assume the probability the team wins each game in Season 1, Season 2, andSeason 3 is 0.45, 0.6, and 0.4, respectively. Let X be the total number of games the teamwins over the three seasons.(a) Use Poisson approximations to binomial distributions to estimate P(X = 260).(b) Use normal approximations to binomial distributions to estimate P(X > 270).

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Answered: (31) A baseball teams plays 182 games…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Let XX represent the full height of a certain species of tree. Assume that XX has a normal probability distribution with a mean of 97.9 ft and a standard deviation of 5.4 ft.A tree of this type grows in my backyard, and it stands 86 feet tall. Find the probability that the height of a randomly selected tree is as tall as mine or shorter.P(X<86)P(X<86) = My neighbor also has a tree of this type growing in her backyard, but hers stands 112.5 feet tall. Find the probability that the full height of a randomly selected tree is at least as tall as hers.P(X>112.5)P(X>112.5) = Enter your answers as decimals accurate to 4 decimal places.
Suppose X is a random variable of uniform distribution between 1 and 7. Find E(X)
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Weights of Lamb after eight weeks after born are normally distributed with mean µ = 14 kg and variance σ 2 = 4. a)Find the probability p that a single lamb has weight less than 12 kg. b) Find the probability that exactly 3 of the next 5 lambs examined will have weights less than 12 kg.
What does the memoryless property refer to? An event cannot occur if it has already occured within a recent specified time period. The distribution of the time until an event does not depend on how much time has already passed. The occurrence of an event is independent of the number of times that event has already occurred. None of the above.
A university is considering setting up an information desk manned by one employee. Based on information obtained from similar information desks, it is believed that people will arrive at the desk at the rate of 18 per hour. It takes an average of 2 minutes to answer a question. It is assumed that arrivals are Poisson and answer times are exponentially distributed. What is the arrival rate? (Include the units.) What is the service rate? (Include the units.) Find the probability that the employee is idle.
Let X represent the number of homes a real estate agent sells during a given month. Based on previous sales records, she estimates that P(0)= 0.62, P(1)= 0.21, P(2)= 0.13, P(3)= 0.03, P(4)= 0.01, with negligible probability for higher values of x. Find the long-term average number of homes the real estate agent expects to sell each month.
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The Poisson distribution gives the probability for the number of occurrences for a "rare" event. Now, let x be a random variable that represents the waiting time between rare events. Using some mathematics, it can be shown that x has an exponential distribution. Let x > 0 be a random variable and let β > 0 be a constant. Then y = 1 β e−x/β is a curve representing the exponential distribution. Areas under this curve give us exponential probabilities. If a and b are any numbers such that 0 < a < b, then using some extra mathematics, it can be shown that the area under the curve above the interval [a, b] is the following. P(a < x < b) = e−a/β − e−b/β Notice that by definition, x cannot be negative, so, P(x < 0) = 0. The random variable x is called an exponential random variable. Using some more mathematics, it can be shown that the mean and standard deviation of x are the following. μ = β and σ = β Note: The number e = 2.71828 is used throughout…
If the number X of particles emitted during a 1-hour period from a radioactive source has a poisson distribution with parameter equal to 4 and that the probability that any emitted is recorded is p=0.9 find the probability distribution of the number Y of the particles recorded in a 1-hour and hence the probability that no particle is recorded
Consider a Poisson distribution with a mean of three occurrences per time period. (a) Write the appropriate Poisson probability function. f(x) = (b) What is the expected number of occurrences in four time periods? (c) Write the appropriate Poisson probability function to determine the probability of x occurrences in four time periods. f(x) = (d) Compute the probability of three occurrences in one time period. (Round your answer to four decimal places.) (e) Compute the probability of twelve occurrences in four time periods. (Round your answer to four decimal places.) (f) Compute the probability of ten occurrences in three time periods. (Round your answer to four decimal places.)

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