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# 4-3_PDF - LECTURE UNIT 4.3 Normal Random Variables and...

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LECTURE UNIT 4.3 Normal Random Variables and Normal Probability Distributions

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Understanding Normal Distributions is Essential for the Successful Completion of this Course
Recall: Probability Distributions p(x) for a Discrete Random Variable p(x) = Pr(X=x) Two properties 1. 0 p(x) 1 for all values of x 2. all x p(x) = 1

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Graph of p(x) ; x binomial n=10 p=.5; p(0)+p(1)+ +p(10)=1 Think of p(x) as the area of rectangle above x  p(5)=.246 is the area of the rectangle above 5 The sum of all the areas is 1
Recall: Continuous r. v. x A continuous random variable can assume any value in an interval of the real line (test: no nearest neighbor to a particular value)

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Discrete rv: prob dist function Cont. rv: density function Discrete random variable p(x) : probability distribution function for a discrete random variable x Continuous random variable f(x) : probability density function of a continuous random variable x
Binomial rv n=100 p=.5

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The graph of f ( x ) is a smooth curve f(x)
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## This note was uploaded on 02/13/2012 for the course BUS 350 taught by Professor Reiland during the Fall '08 term at N.C. State.

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4-3_PDF - LECTURE UNIT 4.3 Normal Random Variables and...

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