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Lecture15 - ECO220Y Lecture 15 Continuous Distribution Part...

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ECO220Y Lecture 15 Continuous Distribution Part 1 Continuous Distribution – Part 1 Migiwa Tanaka Reading: 8.1 1

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O tli Outline Introduction – Discrete vs Continuous Introduction Discrete vs. Continuous Continuous Distribution Examples of Continuous Distribution Uniform Distribution Triangle Distribution Normal Distribution Student t Distribution F Distribution 2
C ti R d V i bl Continuous Random Variable It can take any values within a interval --- infinite possibilities. M i bl i th l ld ti Many variables in the real world are continuous. Height, Weight, Temperature, Speed We may only see finite set of values in data but it is because… Sample size is finite and Our ability to measure is limited. 3

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Discrete vs Continuous Discrete vs. Continuous Discrete Continuous Finite possible values. Probability Distribution Infinitely many possible values Probability Distribution P(X=x)=p(x) = the probability of rv X taking the value x f(X=x)=f(x)=density of r.v. X at value x of r.v. X taking the value x. In distribution diagram, height of distribution =probability value x. Probability can be specified only for a interval of values of distribution =probability.
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Lecture15 - ECO220Y Lecture 15 Continuous Distribution Part...

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