Probability Distribution Essay Example Suppose you flip a coin two times. This simple statistical experiment can have four possible outcomes: HH‚ HT‚ TH‚ and TT. Now‚ let the random variable X represent the number of Heads that result from this experiment. The random variable X can only take on the values 0‚ 1‚ or 2‚ so it is a discrete random variable Binomial Probability Function: it is a discrete distribution. The distribution is done when the results are not ranged along a wide range‚ but are
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understanding of commonly applied management science techniques in the context of business problems. 2. To apply the selected management science techniques in the context of business problems. 3. To discuss the assumptions‚ the advantages and the limitations of each of the management science techniques in solving business related problems. 3. COURSE CONTENTS |DATE |TITLE |HOURS
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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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your credit score‚ the probability that you will be lent to‚ increases. The score itself is determined from credit reports that disclose the individual’s history of financial activity. Their gender‚ race‚ religion‚ nor age play a role. From most influential to least‚ it is composed of a person’s payment history (35%)‚ amount owed (30%)‚ length of history (15%)‚ variety in credit (10%)‚ and a miscellaneous component (10%). Even though that a FICO score is the most popular type of credit score‚ it itself
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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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Probability Distribution Memo To: Howard Gray‚ CEO; Jean Dubois‚ VP Mechanical Watch Division; Uma Gardner‚ VP Production; Amanda Hamilton‚ VP Marketing After identifying the business problem of falling sales and an increase in rejections by the Swiss Official Chronometer Control‚ conducting a study for research will prove to identify a solution. Researchers performed a study of a sample population of 500 people. The study reveals 60% of the watches purchased are certified and the average
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new Household appliance to potential customers. She has found from her years of experience that after demonstration‚ the probability of purchase (long run average) is 0.30. To perform satisfactory on the job‚ the salesperson needs at least four orders this week. If she performs 15 demonstrations this week‚ what is the probability of her being satisfactory? What is the probability of between 4 and 8 (inclusive) orders? Solution p=0.30 q=0.70 n=15 k=4 [pic] Using Megastat we get
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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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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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