The number of chocolate chips in a chocolate chip cookie has a Poisson distribution with parameter 2 = 7.3. Suppose thatthe random variable X is the number of chocolate chips in a randomly selected chocolate chip cookie. Let Y be the totalnumber of chocolate chips in 4 randomly selected chocolate chip cookies. The Poisson distribution is very useful in analyzingphenomena which occur randomly in space or time. Do the calculations below using R.a. For our model, what is expected value of X? 29.2e. What is the smallest integer value C so at least 93% of chocolate chip cookies have no more than C chocolate chips?h. What is the probability Y = 29?j. What is the probability that X>9 given that X>8? 0.647

From the given information, the number of chocolate chips in a cookies has a Poisson distribution…

Answered: The number of chocolate chips in a…

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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the environmental protection agency (EPA) limits the amount of vinyl chloride in the plant air emission to no more than 10 parts per millions. suppose a mean emission of vinyl chloride for a partiular plant is 4 parts per million. assume the number of parts per million of vinyl chloride in air sample x follows a Poisson probability distribution what is the standard deviation of the plant is it likely that a sample of air from the plant would yield a value of x that would exceed the EPA limit? explain. note that P(x <=9)= 0.991868
The U.S. Geological Survey compiled historical data about Old Faithful Geyser (Yellowstone National Park) from 1870 to 1987. Let x1 be a random variable that represents the time interval (in minutes) between Old Faithful eruptions for the years 1948 to 1952. Based on 9180 observations, the sample mean interval was x1 = 62.6 minutes. Let x2 be a random variable that represents the time interval in minutes between Old Faithful eruptions for the years 1983 to 1987. Based on 24,872 observations, the sample mean time interval was x2 = 70.0 minutes. Historical data suggest that σ1 = 8.91 minutes and σ2 = 11.78 minutes. Let μ1 be the population mean of x1 and let μ2 be the population mean of x2. (a) Compute a 95% confidence interval for μ1 – μ2. (Use 2 decimal places.) lower limit upper limit (b) Comment on the meaning of the confidence interval in the context of this problem. Does the interval consist of positive numbers only? negative numbers only? a mix of positive and…
The mean number of customers arriving at a service station during the 25-minute period is 5. Find the probability that 3 or more customers will arrive at the service station during a 25-minute period. Assume that the service system can be modeled as a Poisson distribution
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Let a be a random variable representing the percentage of protein content for early bloom alfalfa hay. The average percentage protein content of such early bloom alfalfa should be u = 17.2%. A farmer's co-op is thinking of buying a large amount of baled hay but suspects that the hay is from a later summer cutting with lower protein content. A small amount of hay was removed from each bale of a random sample of 50 bales. The average protein content from the samples was determined by a local agricultural college to be -15.8% with a sample standard deviation of S = 5.3%- At a = .05, does this hay have lower average protein content than the early bloom alfalfa?
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The times between arrivals in a queue follow an exponential distribution with a rate of 1. Check the incorrect alternative: a) 50% of arrivals will take place before 1 minute. b) If the times between arrivals are exponentially distributed with a rate equal to 1, then arrivals occur according to a Poisson distribution with an average equal to 1. c) Times between arrivals are independent. d) The variance of the times between arrivals is equal to 1. e) There is an average of one arrival every minute.
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A certain type of tree has seedlings randomly dispersed in a large area, with the mean density of seedlings being approximately three per square yard. If the seedlings are randomly dispersed, the number of seedlings per region, Y can be modelled as a Poisson random variable. If a 1 forester randomly locates ten 1-square-yard sampling regions in the area, the probability that none of the regions will contain seedlings is 0.0498. 2.3.1 If the seedlings really are randomly dispersed, the number of seedlings per region, Y, can be modelled as a Poisson random variable with 2 = 3. Interpret 1 =3. 2.3.2 State the moment generating function_of the random variable Y.

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