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Suppose that the number of flaws in a randomly selected glass sheet follows a Poisson distribution with parameter λ=0.7. The Poisson distribution is a discrete probability distribution specified by a single parameter λ, where λ is a positive real number. In this particular case, λ=0.7 is the mean number of flaws per sheet. For Poisson distribution with a parameter λ, the mean is λ and its variance is also λ. First, you will study the distribution of the number of flaws in a randomly selected glass sheet (population distribution). Select the Poisson option in the Calculator tool in the Data menu. Enter the value of the mean λ=0.7. The applet Poisson enables you to calculate Poisson probabilities and display the corresponding probability distribution function. Use the applet to answer the following questions:
(a) What is the shape of a distribution of the number of flaws in a randomly selected glass sheet ? Is it symmetric or skewed? What does the shape say about the typical number of flaws in a randomly selected glass sheet?
(b) What is the probability that there are no flaws in a randomly selected sheet? In other words, what is the fraction of glass sheets in perfect condition?
(c) Consider boxes consisting of 5 glass sheets (random samples of 5). What is the percentage of samples with all 5 sheets in perfect condition (no flaw). Given the large number of glass sheets in the production run, you can assume independence between glass sheets.
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in some reports the mean and coefficient of variation are given. for instance in statistical abstract of the united
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Physical Sciences Carlinville, Illinois, has just started an ambitious recycling program. Special trucks collect recyclable products once a week.
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