Chapter4

Chapter4 - Chapter 4 Discrete Random Variables Denition 4.1...

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Chapter 4 Discrete Random Variables Defnition 4.1 Random Variable : A numerical variable whose value depends on outcome of a chance experiment is called a random variable . OR A random variable is a variable that assumes numerical values associated with the random outcomes of an experiment, where one (and only one) numerical value is assigned to each sample point. 4.1 Two Types oF Random Variables Defnition 4.2 Discrete Random Variable: A discrete random variable is one that can assume a countable number of values. Example i : The number of automobiles sold per month. Example ii : The number of car accidents on a particular day in a City. Example 4.2, page 175. Defnition 4.3 Continuous Random Variable: A continuous random variable is one that can assume the inFnitely many values corresponding to the points on a line interval. Example i: The amount of petroleum pumped per hour from a Gas station. Example ii: The heights of the students in this class. Example 4.3, page 176. Exercise 4.1, page 177. 4.2 Probability Distributions For Discrete Random Vari- ables Defnition 4.4 Probability Distribution: The probability distribution for a discrete random variable is a display that gives the possible values of x along with their corresponding probabilities of occurrence, p ( x ). This probability distribution can be represented by a formula, table or a graph. 24
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Two important characteristics of any probability distribution, which are given as follows 1. 0 p ( x ) 1, for all values of x . 2. P ( x ) = 1, where the sum is over all possible values of x . Example 4.4, page 177. Exercise 4.12, page 183.
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This note was uploaded on 09/15/2011 for the course STA 2023 taught by Professor Mcguckian during the Fall '08 term at FIU.

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Chapter4 - Chapter 4 Discrete Random Variables Denition 4.1...

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