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Unformatted text preview: Administration 1. Midterm 2, Wednesday, November 9th. 810PM, 155 Dwinelle. 2. HKN Midterm Review, Sunday, November 6th, 24, 306 Soda. (Can someone confirm?) 3. Midterm Review, Sunday, November 6th. 57PM, 155 Dwinelle. 4. Extra office hours: Tuesday, November 8th, 49PM, 310 Soda. CS70: Satish Rao: Lecture 28. 1. Joint Distributions Multiple Random Variables. Experiment: Outcome: ω Variables: X ( ω ) and Y ( ω ) . Multiple Random Variables. Experiment: Outcome: ω Variables: X ( ω ) and Y ( ω ) . Roll two die: Outcome: ( x , y ) . Result of both rolls! X is value of first. Y is value of second. Multiple Random Variables. Experiment: Outcome: ω Variables: X ( ω ) and Y ( ω ) . Roll two die: Outcome: ( x , y ) . Result of both rolls! X is value of first. Y is value of second. Choose a person at random: X is height. Y is weight. Multiple Random Variables. Experiment: Outcome: ω Variables: X ( ω ) and Y ( ω ) . Roll two die: Outcome: ( x , y ) . Result of both rolls! X is value of first. Y is value of second. Choose a person at random: X is height. Y is weight. Binomial: flip n coins. X i : “indicator” random variable for heads on coin i i.e., X i = 1 if i th coin is heads, 0 otherwise. Multiple Random Variables. Experiment: Outcome: ω Variables: X ( ω ) and Y ( ω ) . Roll two die: Outcome: ( x , y ) . Result of both rolls! X is value of first. Y is value of second. Choose a person at random: X is height. Y is weight. Binomial: flip n coins. X i : “indicator” random variable for heads on coin i i.e., X i = 1 if i th coin is heads, 0 otherwise. What is distribution of these random variables? Multiple Random Variables. Experiment: Outcome: ω Variables: X ( ω ) and Y ( ω ) . Roll two die: Outcome: ( x , y ) . Result of both rolls! X is value of first. Y is value of second. Choose a person at random: X is height. Y is weight. Binomial: flip n coins. X i : “indicator” random variable for heads on coin i i.e., X i = 1 if i th coin is heads, 0 otherwise. What is distribution of these random variables? Distribution of X and distribution of Y . Multiple Random Variables. Choose a person at random: X is height. Y is weight. Multiple Random Variables. Choose a person at random: X is height. Y is weight. Distribution of X and Y are fine..but Multiple Random Variables. Choose a person at random: X is height. Y is weight. Distribution of X and Y are fine..but if someone is taller, might s/he be heavier? Multiple Random Variables. Choose a person at random: X is height. Y is weight. Distribution of X and Y are fine..but if someone is taller, might s/he be heavier? Binomial: flip n coins. X i : “indicator” random variable for heads on coin i i.e., X i = 1 if i th coin is heads, 0 otherwise. Multiple Random Variables....
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 Fall '11
 Rau
 Probability distribution, Probability theory, probability density function, symptons

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