PPT-6A Binomial and Poisson

mean and variance Binomial Distribution KUS objectives BAT use formulas to find the mean and variance of the binomial distribution Starter A company is searching for oil reserves The company has purchased the rights to make test drillings at four sites It investigates these sites one at a time but if oil is found it does not proceed to any further sites At each site there is probability 039 of finding oil independently of all other sites The random variable . Delta On-Time Performance at Hartsfield-Jackson Atlanta International (June, 2003 - June, 2015). http://www.transtats.bts.gov/OT_Delay/ot_delaycause1.asp?display=data&pn=1. Data / Model. Total Operations: 2,278,897. Zhang . Zhuozhuo. . Calum. Johnson . Waldemar. . Pietraszkiewicz. . The binomial model is a very useful and popular technique for pricing an option.. The binomial option pricing formula is based on assumption that the stock price follows a multiplicative binomial process over discrete intervals. . Karl L. Wuensch. Department of Psychology. East Carolina University. A Binomial . Experiment. consists of . n. identical trials.. each trial results in one of two outcomes, a “success” or a “failure.”. Shane G. Henderson. http://people.orie.cornell.edu/~shane. A Traditional Definition. Shane G. Henderson. 2. /15. What . A. re . T. hey For?. Shane G. Henderson. 3. /15. Times of customer arrivals (no scheduling and no groups). The Poisson random variable was first introduced by the French mathematician Simeon-Denis Poisson (1781-1840). He discovered it as a limit to the binomial distribution as the number of trials . n. approaches infinity.. http://www.answers.com/topic/binomial-distribution. Chapter 18: Poisson Random Variables. http://. www.boost.org/doc/libs/1_35_0/libs/math/doc/sf_and_dist/html. /. math_toolkit. /. dist. /. dist_ref. Quantitative Analysis for Business Decisions. 2. 4.6 Standard Discrete Distributions continued. Further Examples on Use. Example 5. : . The probability of a . good. component in inspecting assembly line output is known to be 0.8 ; probability of a . . and Exponential Distributions. 5. Introduction. Several specific distributions commonly occur in a variety of business situations:. N. ormal distribution—a continuous distribution . characterized . 1. Discrete Data. All data comes in Discrete form.. For Measurement data, in principle, it is on a continuous scale, but in reality it is truncated. . As long as Sigma(X)>measurement unit, there is no problem with using charts.. Delta On-Time Performance at Hartsfield-Jackson Atlanta International (June, 2003 - June, 2015). http://www.transtats.bts.gov/OT_Delay/ot_delaycause1.asp?display=data&pn=1. Data / Model. Total Operations: 2,278,897. Ch. 3 . Myung Song, Ph.D.. © 2009 W.H. Freeman and Company. 1.. 2. Random Variables. Definition. For a given sample space S of some experiment, a . random variable (. rv. ) . is any . rule that associates a number with each outcome in S . . 6.3: Binomial and Geometric Random Variables After this section, you should be able to… DETERMINE whether the conditions for a binomial setting are met COMPUTE and INTERPRET probabilities involving binomial random variables Lecture 1. Harrison B. Prosper. Florida State University. European School of High-Energy Physics. Parádfürdő. , Hungary. . 5 . – . 18 . June, . 2013. 1. Outline. Lecture 1. Descriptive Statistics. Sit with your group and choose a team name. Preferably something corny that has to do with statistics . Today’s game will test your strength, wit, knowledge, and endurance! Remember… HW Passes are at stake folks! May the force be with you!.