PPT-Chapter 6 Random Variables

Section 61 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. 1 Sums of Discrete Random Variables In this chapter we turn to the important question of determining the distribution of a sum of independent random variables in terms of the distributions of the individual constituents In this section we consider on 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 Expected Value. Airline overbooking. Pooling . blood . samples. Variance and Standard . Deviation . Independent Collections. Optimization. DECS 430-A. Business Analytics . I: Class 2. Random Variables. 1.1 What Is "Probability"?. 1.2 The Additive Law. 1.3 Conditional Probability and Independence. 1.4 Permutations and Combinations. 1.5 Continuous Random Variables. 1.6 . Countability. and Measure Theory. 1. http://www.landers.co.uk/statistics-cartoons/. 5.1-5.2: Random Variables - Goals. Be able to define what a random variable is.. Be able to differentiate between discrete and continuous 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//. 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.. Applied Statistics and Probability for Engineers. Sixth Edition. Douglas C. Montgomery George C. . Runger. Chapter 5 Title and Outline. 2. 5. Joint Probability Distributions. 5-1 Two or More Random Variables. 1. 5. Joint Probability Distributions. 5-1 Two or More Random Variables. 5-1.1 Joint Probability Distributions. 5-1.2 Marginal Probability Distributions. 5-1.3 Conditional Probability 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. Random Variables Expected Value Airline overbooking Pooling blood samples Variance and Standard Deviation Independent Collections Optimization DECS 430-A Business Analytics I: Class 2 Random Variables Objective. : . Use experimental and theoretical distributions to make judgments about . the . likelihood of various outcomes in uncertain . situations. CHS Statistics. Decide if the following random variable x is discrete(D) or continuous(C). . 1. http://www.landers.co.uk/statistics-cartoons/. 5.1-5.2: Random Variables - Goals. Be able to define what a random variable is.. Be able to differentiate between discrete and continuous random variables..