285%2Bchap04-P2

285%2Bchap04-P2 - Statistics Chapter 4 Random Variables and...

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Chap 6-1 Statistics Chapter 4 Random Variables and Probability Distributions - Continuous Sections 4.5-4.8
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Chap 6-2 Probability Distributions Continuous Probability Distributions Binomial Hypergeometric Poisson Probability Distributions Discrete Probability Distributions Normal Uniform Exponential
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Chap 6-3 Continuous Probability Distributions A continuous random variable is a variable that can assume any value on a continuum (can assume an uncountable number of values) thickness of an item time required to complete a task temperature of a solution height, in inches These can potentially take on any value, depending only on the ability to measure accurately.
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Chap 6-4 The Normal Distribution Continuous Probability Distributions Probability Distributions Normal Uniform Exponential
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Chap 6-5 The Normal Distribution Bell Shaped Symmetrical Mean, Median and Mode are Equal Location is determined by the mean, μ Spread is determined by the standard deviation, σ The random variable has an infinite theoretical range: + to - Mean = Median = Mode x f(x) μ σ
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Chap 6-6 By varying the parameters μ and σ , we obtain different normal distributions Many Normal Distributions
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Chap 6-7 The Normal Distribution Shape x f(x) μ σ Changing μ shifts the distribution left or right. Changing σ increases or decreases the spread.
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Chap 6-8 Finding Normal Probabilities a b x f(x) P a x b ( ) Probability is measured by the area under the curve
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Chap 6-9 f(x) x μ Probability as Area Under the Curve 0.5 0.5 The total area under the curve is 1.0 , and the curve is symmetric, so half is above the mean, half is below 1.0 ) x P( = < < -∞ 0.5 ) x P(μ = < < 0.5 μ) x P( = < <
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Chap 6-10 Empirical Rules μ ± 1 σ encloses about 68% of x’s f(x) x μ μ
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This note was uploaded on 03/23/2011 for the course STATS 100 taught by Professor Lawerence during the Spring '11 term at Rutgers.

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285%2Bchap04-P2 - Statistics Chapter 4 Random Variables and...

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