MATH 1342 CHAPTER 6 OH

MATH 1342 CHAPTER 6 OH - CHAPTER 6 DISCRETE PROBABILITY...

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CHAPTER 6: DISCRETE PROBABILITY DISTRIBUTIONS
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PROBIBILITY DISTRIBUTION DEFINITIONS: Random Variable is a measurable or  countable  outcome of a probability  experiment. Discrete Random Variables have  countable  and finite outcomes. Continuous Random Variables have  infinitely many possible outcomes from  measurements  and are described in  ranges of values.
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DISCRETE PROBABILITY DISTRIBUTIONS: Looks like Discrete Relative Frequency  Distributions from chapter 2. The relative frequency is the probability  [p(x)] of the discrete value (x) occurring  and therefore has a value between 0 and  1. The sum of all probabilities is 1.0.
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DISCRETE PROBABILITY DISTRIBUTIONS: Example of rolling a pair of dice. Make up of Jury in area that is 45%  Hispanic.
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DISCRETE PROBABILITY DISTRIBUTIONS: Mean of the  distribution: Std. Dev. of the  Distribution: Calculator: ( 29 * ( ) x p x μ= ( 29 2 2 * ( ) x p x σ μ = - 1 ( ) 2 1 _ 1, 2 x L p x L STATS CALC VARSTATS L L → -
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EXPECTED VALUE: Same as discrete probability distribution but  some outcomes may be negative. Calculated same as mean of discrete probability  distribution: Example of raffle. Example of lottery. Example of insurance. [ ] . . * ( ) EV outcome p outcome =
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DISTRIBUTION: Calculate the probability of rolling a die five  times and getting a “1” exactly 2 times. p=1/6, n=5, 1-p=5/6. How many ways can this happen. Do the same for 0, 1, 3, 4 and 5 times.
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This note was uploaded on 01/07/2012 for the course MATH 1342 taught by Professor Lisajuliano during the Fall '12 term at Collins.

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MATH 1342 CHAPTER 6 OH - CHAPTER 6 DISCRETE PROBABILITY...

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