intro to probability notes

intro to probability notes - the possible values of the...

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Probability What is probability – what does it represent? Why is the study of probability important (I thought this was a statistics class!?!) Some terms: sample space, outcome, event How do we represent it symbolically? P[A] – what does that mean? Some rules for probabilities 1. 2. 3. But these rules don’t fix probabilities – so how do we decide on what probabilities ought to be? 1. 2. 3. Random Variable Definition: a function which assigns a real number to every outcome of an experiment. (I.e., the outcome of the experiment we are interested in is numerical.) Typically denoted by a capital letter - X, R, T, Y, Z; (let corresponding lower case letter denote
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Unformatted text preview: the possible values of the random variable). Consider P[X=x] in place of P[A], or P[X ≤ x], P[0 ≤ X ≤ 5], P[X=0 or X=1 or X=2] There are two types of random variables (we need to be able to distinguish readily): we handle them similarly but not exactly the same way.- Discrete random variables – take on only a countable number of values (typically whole numbers, but not necessarily) X=1, 2, or 3 Y = 0, 1, 2, 3, ….- Continuous random variables – take on values on some interval of the real line 0 ≤ P ≤ 1 0 ≤ T < ∞ -∞ < Z < ∞ intro to probability...
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This note was uploaded on 02/01/2012 for the course STAT 490 taught by Professor Boyer during the Spring '11 term at Kansas State University.

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