PPT-Part VI: Named Continuous Random Variables

Author : liane-varnes | Published Date : 2017-06-03

httpwwwusersyorkacukpml1bayescartoonscartoon08jpg 1 Comparison of Named Distributions discrete continuous Bernoulli Binomial Geometric Negative Binomial Poisson

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Part VI: Named Continuous Random Variables: Transcript

httpwwwusersyorkacukpml1bayescartoonscartoon08jpg 1 Comparison of Named Distributions discrete continuous Bernoulli Binomial Geometric Negative Binomial Poisson Hypergeometric Discrete Uniform. RANDOM VARIABLES Definition usually denoted as X or Y or even Z and it is th e numerical outcome of a random process Example random process The number of heads in 10 tosses of a coin Example The number 5 rating Jake Blanchard. Spring 2010. Uncertainty Analysis for Engineers. 1. Introduction. We’ve discussed single-variable probability distributions. This lets us represent uncertain inputs. But what of variables that depend on these inputs? How do we represent their uncertainty?. QSCI 381 – Lecture 12. (Larson and Farber, Sect 4.1). Learning objectives. Become comfortable with variable definitions. Create and use probability distributions. Random Variables-I. A . http://www-users.york.ac.uk/~pml1/bayes/cartoons/cartoon08.jpg. 1. Comparison of Named Distributions. discrete. continuous. Bernoulli,. Binomial, Geometric, Negative Binomial, Poisson, Hypergeometric, Discrete Uniform. Expected Value. Airline overbooking. Pooling . blood . samples. Variance and Standard . Deviation . Independent Collections. Optimization. DECS 430-A. Business Analytics . I: Class 2. Random Variables. http://. rchsbowman.wordpress.com/2009/11/29. /. statistics-notes-%E2%80%93-properties-of-normal-distribution-2/. Chapter 23: Probability Density Functions. http://. divisbyzero.com/2009/12/02. /. an-applet-illustrating-a-continuous-nowhere-differentiable-function//. 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. Random Variables. Definition:. A rule that assigns one (and only one) numerical value to each simple event of an experiment; or. A function that assigns numerical values to the possible outcomes of an experiment.. . 4.1 - . Probability Density Functions. 4.2 - Cumulative Distribution . Func. tions. and. . . . Expected Values. . . 4.3 - The Normal Distribution. . 4.4 - . The Exponential and Gamma Distributions. Random Variables. Definition:. A rule that assigns one (and only one) numerical value to each simple event of an experiment; or. A function that assigns numerical values to the possible outcomes of an experiment.. adding . constants to random variables, multiplying random variables by constants, and adding two random variables together. AP Statistics B. pp. 373-74. 1. Pp. 373-74 are just plain hard. I don’t like the way they are written. http://www.answers.com/topic/binomial-distribution. Chapter 13: Bernoulli Random Variables. http://www.boost.org/doc/libs/1_42_0/libs/math/doc/sf_and_dist/html. /. math_toolkit. /. dist. /. dist_ref. Section 6.1. Discrete & Continuous Random Variables. After this section, you should be able to…. APPLY the concept of discrete random variables to a variety of statistical settings. CALCULATE and INTERPRET the mean (expected value) of a discrete random variable. Section 6.1. Discrete and Continuous. Random Variables. Discrete and Continuous Random Variables. USE the probability distribution of a discrete random variable to CALCULATE the probability of an event..

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