LECTURE UNIT 4.3 Normal Random Variables and Normal Probability Distributions.

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LECTURE UNIT 4.3 Normal Random Variables and Normal Probability Distributions

Transcript of LECTURE UNIT 4.3 Normal Random Variables and Normal Probability Distributions.

Page 1: LECTURE UNIT 4.3 Normal Random Variables and Normal Probability Distributions.

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

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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 areaof rectangle above x

p(5)=.246 is the areaof the rectangle above 5

The sum of all theareas is 1

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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 functionCont. 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

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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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Graphs of probability density functions f(x)

Probability density functions come in many shapes

The shape depends on the probability distribution of the continuous random variable that the density function represents

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Graphs of probability density functions f(x)

f(x)

f(x) f(x)

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a b

Probabilities:area undergraph of f(x)

P(a < X < b) = area under the density curve between a and b.

P(X=a) = 0

P(a < x < b) = P(a < x < b)

f(x)P(a < X < b)

X

P(a X b) = f(x)dxa

b

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Properties of a probability density function f(x)

f(x)0 for all x the total area under the

graph of f(x) = 1

0 p(x) 1 p(x)=1

Think of p(x) as the areaof rectangle above x

The sum of allthe areas is 1

xx

Total areaTotal areaunder curveunder curve

=1=1

f(x)f(x)

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Important difference

1. 0 p(x) 1 for all values of x

2. all x p(x) = 1

values of p(x) for a discrete rv X are probabilities: p(x) = Pr(X=x);

1. f(x)0 for all x

2. the total area under the graph of f(x) = 1

values of f(x) are not probabilities - it is areas under the graph of f(x) that are probabilities

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