STAT 2060 Chapter Notes - Chapter 4: Probability Plot, Central Limit Theorem, Statistic
3 Feb 2013
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Random variable- variable that assumes numerical values associated with the random outcomes of an experiment, where one (and only one) numerical value is assigned to each sample point (ie. values that are infinite and uncountable) are called continuous. Those that assume countable number (infinite or infinite) of values are called discrete. Those that assume values corresponding to any of the points contained in one or more intervals. Requirements for the probability distribution of a discrete random variable, x. The mean or expected value of a discrete random variable: =e(x)= . The variance of a discrete random variable x is: 2=e [(x- )2]= . The standard deviation of a discrete random variable is equal to the square root of the variance (ie. probability rules for a discrete random variable: P( < x < + ) Applies to any probability distribution that are mound shaped and symmetric.
