ECON 221 Lecture 8: ECON221 Lecture 8 CH5

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Random variable: function that assigns numerical values to outcomes of an experiment, expressed as upper case letters, usually summarizes outcomes of an experiment with numerical values. Random variables have two classifications: discrete: numerical values are countable, continuous: numerical values are not countable, infinite numbers. Probability distribution: probability mass function (pmf): describes discrete random variables, probability density function: describes to describe continuous variables (chapter 6, cumulative distribution function (cmf): describes both discrete and continuous variables. Pmf formula: goes from numbers to numbers. Important probabilities of discrete probability distributions: probability of each value is between 0 and 1 or should be equal, the sum of the probabilities should equal 1, can be seen as a table, graph, or formula. Cmf: probability of a random value is less than or equal to the value of. (cid:4666) (cid:4667) (cid:883) for largest values of in the sample space. (cid:4666) (cid:4667) (cid:882) for smallest values of in the sample space.

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