probability questions : 1. A real estate office has been averaging 1.8 sales per day for the past several months. What is the probability that the office will make 4 sales today? .0723 2. A washing machine in a Laundromat breaks down an average of two times per month. What is the probability that the machine will break down more than 28 times in the next year? .1775 3. Flaws occur randomly in a particular fabric with a mean rate of occurance of 1.5 every 5 sqare yards. If you purchase 20 square
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companies and the probability of getting a job offer there. These data are tabulated below. The tabulation is in the decreasing order of cost. 1. If the graduate applies to all 10 companies‚ what is the probability that she will get at least one offer? 2. If she can apply to only one company‚ base on cost and success probability criteria alone‚ should she apply to company 5? Why or why not? 3. If she applies to companies 2‚5‚8‚ and 9‚ what is the total cost? What is the probability that she will
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positions are filled at random form the 11 finalists‚ what is the probability of selecting: A: 3 females and 2 males? B: 4 females and 1 male? C: 5 females? D: At least 4 females? Problem 2 By examining the past driving records of drivers in a certain city‚ an insurance company has determined the following (empirical) probabilities: [pic] If a driver in this city is selected at random‚ what is the probability that: A: He or she drives less than 10‚000 miles per year or has
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The Poisson probability distribution‚ named after the French mathematician Siméon-Denis. Poisson is another important probability distribution of a discrete random variable that has a large number of applications. Suppose a washing machine in a Laundromat breaks down an average of three times a month. We may want to find the probability of exactly two breakdowns during the next month. This is an example of a Poisson probability distribution problem. Each breakdown is called an occurrence in Poisson
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The Collier Encyclopedia’s definition for probability is the concern for events that are not certain and the reasonableness of one expectation over another. These expectations are usually based on some facts about past events or what is known as statistics. Collier describes statistics to be the science of the classification and manipulation of data in order to draw inferences. Inferences here can be read to mean expectations‚ leading to the conclusion that the two go hand in hand in accomplishing
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14. If x has the probability distribution f(x) = 12x for x = 1‚2‚3‚…‚ show that E(2X) does not exist. This is famous Petersburg paradox‚ according to which a player’s expectation is infinite (does not exist) if he is to receive 2x dollars when‚ in a series of flips of a balanced coin‚ the first head appears on the xth flip. 17. The manager of a bakery knows that the number of chocolate cakes he can sell on any given day is a random variable having the probability distribution f(x) = 16 for x =
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Overview | | | |The Process of Quantitative Modeling | | | |Review of Probability Concepts
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results from 100 strands are as follows: High conductivity Low conductivity Strength High Low 74 8 15 3 (a) If a strand is randomly selected‚ what is the probability that its conductivity is high and its strength is high? P (High conductivity and high strength)= 74/100 =0.74 (b) If a strand is randomly selected‚ what is the probability that its conductivity is low or its strength is low? P (Low strength or low conductivity) = P(Low conductivity) + P(Low strength) – P(Low conductivity and low
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M227 Chapter 1 Nature of Probability and Statistics OBJECTIVES Demonstrate knowledge of statistical terms. Differentiate between the two branches of statistics. Identify types of data. Identify the measurement level for each variable. Identify the four basic sampling techniques. Explain the difference between an observational and an experimental study. Explain how statistics can be used and misused. Explain the importance of computers and calculators in statistics. Statistics is the science
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Statistics Chapter 5 Some Important Discrete Probability Distributions 5-1 Chapter Goals After completing this chapter‚ you should be able to: Interpret the mean and standard deviation for a discrete probability distribution Explain covariance and its application in finance Use the binomial probability distribution to find probabilities Describe when to apply the binomial distribution Use Poisson discrete probability distributions to find probabilities 5-2 Definitions Random Variables A
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