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Unformatted text preview: Lecture 2: Discrete Distributions, Normal Distributions Chapter 1 Reminders • Course website: – www. stat.purdue.edu/~xuanyaoh/stat350 • Office Hour: Mon 3:304:30, Wed 45 • Bring a calculator, and copy Tables I – III. • Start Hw#1 now. – Due by beginning of Next Fri class Exercise 1 Exponential Distribution Terminology Discrete Distributions • Discrete variables are treated similarly but are called mass functions instead of densities • Example: toss a (fair) dice – X can take any discrete value 1, 2, 3, 4, 5, or 6 – Suppose you can throw a dice forever, you can imagine that you will get each number 1/6 of the time – The mass function will be a table, instead of a curve. • What is the mass function of tossing a single dice? Answer: Mass functions • Similar to density functions, the mass function follows 3 properties: Another example—tossing a coin • Suppose you toss a coin 10 times. Let x = the number of heads in 10 tosses. – What are the possible values of x ? – What is the mass function? (We’ll come back to this later) – Here x actually follows a Binomial Distribution • x has a Binomial mass function • x is Binomially distributed Specific distributions • We now look at several important distributions • Continuous – Normal • Discrete – Binomial – Poisson 1.4 1....
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This note was uploaded on 02/06/2012 for the course STAT 350 taught by Professor Staff during the Spring '08 term at Purdue.
 Spring '08
 Staff
 Normal Distribution

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