Special Probability Distributions Chapter 8 Ibrahim Bohari bibrahim@preuni.unimas.my LOGO Binomial Distribution Binomial Distribution In an experiment of n independent trials‚ where p is a the probability of a successful outcome q=1-p is the probability that the outcome is a failure If X is a random variable denoting the number of successful outcome‚ the probability function of X is given P X r nCr p r q nr Where q=1-p r=0‚1‚2‚3‚….. X~B(n‚p) The n trials
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GEMA 5400 | Brunswick Distribution Inc | Case Analysis | | | | Table of Contents Introduction ………………………………………………………………..1 Executive Summary ……………………………………………………2 Application and Analysis ……………………………………………..3 Literature Review………………………………………………………….4 Conclusion……………………………………………………………………..5 Bibliography…………………………………………………………………..6 Appendix…………………………………………………………………………7 INTRODUCTION Brunswick Distribution started as a small distribution company 10 years ago when
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#1 True or false: Even if the sample size is more than 1000‚ we cannot always use the normal approximation to binomial. Solution: If a sample is n>30‚ we can say that sample size is sufficiently large to assume normal approximation to binomial curve. Hence the statement is false. #2 A salesperson goes door-to-door in a residential area to demonstrate the use of a new Household appliance to potential customers. She has found from her years of experience that after demonstration‚ the
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Question 1 The following table gives the classification of the amount paid and the method of payment at a department store. Cash Credit Debit Total < $20 10 8 6 24 $20 - $100 15 25 10 50 Over $100 5 15 6 26 Total 30 48 22 100 a) Find the probability that the amount paid is < $20 Answer: P(<$20) = b) Find the probability that the method of payment is credit Answer: P(Credit) = c) Find the probability that the amount is <$20 and the method of payment
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Chapter 6 Continuous Probability Distributions Case Problem: Specialty Toys 1. Information provided by the forecaster At x = 30‚000‚ [pic] [pic] Normal distribution [pic] [pic] 2. @ 15‚000 [pic] P(stockout) = 1 - .1635 = .8365 @ 18‚000 [pic] P(stockout) = 1 - .3483 = .6517 @ 24‚000 [pic] P(stockout) = 1 - .7823 = .2177 @ 28‚000 [pic]
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Sean Worang Sustainability 04/19/12 Runa Supply Chain I. Farmers Runa has worked with about 3000 to 4500 Guayusa farmers in the Amazon in regards to the supply and distribution of Guayusa leafs. The result of surveys (done by Runatarpuna) shows that by incorporating above 3000 to 4500 farmers Runa can generate about 16000 pounds/ month and can potentially generate about $17.2 per year projections. II. Runatarpuna Runatarpuna is Runa LLC’s fully owned export subsidiary‚ to manage
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F-distribution: A continuous right-skewed statistical distribution also Known as Snedecor’s F distribution or the Fisher - Snedecor distribution ( After R.A. Fisher and George W. Snedecor)(2) which arises in the testing of whether two observed samples have the same variance. (1) Note that three of the most important distributions (namely the normal distribution‚ the t distribution‚ and the chi-square distribution) may be seen as special cases of the F distribution: (3) Example: We want to
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LocatingMiddlemen The search for prospective middlemen should begin with study of the market and determination of criteria for evaluating middlemen servicing that market. The company ’s broad policy guidelines should be followed‚ but expect expediency to override policy at times. The checklist of criteria differs according to the type of middlemen being used and the nature of their relationship with the company. Basically‚ such lists are built around four subject areas: (1) productivity or
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Chapter 13: Chi-Square Applications SHORT ANSWER 1. When samples of size n are drawn from a normal population‚ the chi-square distribution is the sampling distribution of = ____________________‚ where s2 and are the sample and population variances‚ respectively. ANS: PTS: 1 OBJ: Section 13.2 2. Find the chi-square value for each of the right-tail areas below‚ given that the degrees of freedom are 7: A) 0.95 ____________________ B) 0.01 ____________________ C) 0.025 ____________________
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2.3. The Chi-Square Distribution One of the most important special cases of the gamma distribution is the chi-square distribution because the sum of the squares of independent normal random variables with mean zero and standard deviation one has a chi-square distribution. This section collects some basic properties of chi-square random variables‚ all of which are well known; see Hogg and Tanis [6]. A random variable X has a chi-square distribution with n degrees of freedom if it is a gamma
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