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
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CHEMICALS | INCORPORATION OF GALLANT CHEMICALS: MEMORANDUM OF ASSOSIATION: THE COMPANIES ORDINANCE‚ 1984 (PRIVATE COMPANY LIMITED BY SHARES) MEMORANDUM OF ASSOCIATION OF GALLANT CHEMICALS PRIVATE LIMITED 1) The name of the Company is "GALLANT CHEMICALS PRIVATE LIMITED." 2) The Registered Office of the Company will be situated in the province of BALOCHISTAN. 3) The objects for which the Company is established are: * To carry on the business of manufacturers‚ producers
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The T-Distribution and T-Test “In probability and statistics‚ Student ’s t-distribution (or simply the t-distribution) is a continuous probability distribution that arises when estimating the mean of a normally distributed population in situations where the sample size is small” (Narasimhan ‚ 1996). Similar to the normal distribution‚ the t-distribution is symmetric and bell-shaped‚ but has heavier tails‚ meaning that it is more likely to produce values far from its mean. This makes the t-distribution
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1. Excecutive Summary 1.0 Introduction FRANKROJEIAN Snack House start-up a small bakery that rent in 1.1 The Company FRANKROJEIAN Snack House is a Partnership business‚ this will be under supevision of the five partners as the owner of the business. The business wiill be renting a space at the Sienna building Alunan Avenue near government offices‚ schools and private sectors. 1.2 The Products and Servies FRANKROJEIAN Snack House offers the following food and beverages to customers • Cakes
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“dispersion” or variability of the data about the measurements of central tendency. MEASUREMENTS OF CENTRAL TENDENCY The appropriateness of using the mean‚ median‚ or mode in data analysis is dependent upon the nature of the data set and its distribution (normal vs non-normal). The mean (denoted by x) is calculated by dividing the sum of the individual data points (where Σ equals “sum of”) by the number of observations (denoted by n). It is the arithmetic average of the observations and is used
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treaties‚ audio and video files and video games advanced by terrorists’ organizations or sympathizers. Nevertheless‚ what constitutes terrorist propaganda‚ as opposed to legitimate advocacy of a viewpoint‚ is often a subjective valuation. Further‚ the distribution of propaganda is generally not‚ in and of itself‚ a prohibited activity. One of the basic canons of international law is the protection of fundamental
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Competing coffee companies Industry Analysis According to Starbucks corporation‚ 66 billion cups of coffee are drunk every year in the U.S. and a full three quarters of those cups of coffee are enjoyed at home. The other 25% of coffee is drunk at the office‚ traveling‚ or in a coffee shop (CNN Money). Starbucks has no clear competition; however the closest competitors include other specialty coffee shops‚ doughnut shops‚ and restaurants. Starbucks holds a dominant position in the specialty coffeehouse
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Binomial‚ Bernoulli and Poisson Distributions The Binomial‚ Bernoulli and Poisson distributions are discrete probability distributions in which the values that might be observed are restricted to being within a pre-defined list of possible values. This list has either a finite number of members‚ or at most is countable. * Binomial distribution In many cases‚ it is appropriate to summarize a group of independent observations by the number of observations in the group that represent one of
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AMA470 Midterm exam March 5‚ 2010 Please show full working out in order to obtain full marks. 1. Suppose that: • The number of claims per exposure period follows a Poisson distribution with mean λ = 110. • The size of each claim follows a lognormal distribution with parameters µ and σ 2 = 4. • The number of claims and claim sizes are independent. (a) Give two conditions for full credibility that can be completely determined by the information above. Make sure to define all terms in your definition
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Discrete and Continuous Probability All probability distributions can be categorized as discrete probability distributions or as continuous probability distributions (stattrek.com). A random variable is represented by “x” and it is the result of the discrete or continuous probability. A discrete probability is a random variable that can either be a finite or infinite of countable numbers. For example‚ the number of people who are online at the same time taking a statistics class at CTU on
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