Lecture15 - ECO220Y Lecture 15 ontinuous Distribution art 1...

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Unformatted text preview: ECO220Y Lecture 15 ontinuous Distribution art 1 Continuous Distribution Part 1 Migiwa Tanaka Reading: 8.1 1 Outline troduction iscrete vs Continuous Introduction Discrete vs. Continuous Continuous Distribution Examples of Continuous Distribution Uniform Distribution Triangle Distribution Normal Distribution Student t Distribution Distribution F Distribution 2 Continuous Random Variable can take any values within a interval - finite It can take any values within a interval --- infinite possibilities. i bl i th l ld ti Many variables in the real world are continuous. Height, Weight, Temperature, Speed e may only see finite set of values in data but it is We may only see finite set of values in data but it is because mple size is finite and Sample size is finite and Our ability to measure is limited. 3 iscrete vs Continuous Discrete vs. Continuous Discrete Continuous Finite possible values. Probability Distribution Infinitely many possible values Probability Distribution obab ty st but o P(X=x)=p(x) = the probability f v taking the value x f(X=x)=f(x)=density of r.v. X at lue x of r.v. X taking the value x....
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This note was uploaded on 03/01/2011 for the course ECON 220 taught by Professor Tanaka during the Spring '11 term at University of Toronto- Toronto.

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Lecture15 - ECO220Y Lecture 15 ontinuous Distribution art 1...

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