STAT 1030 Study Guide - Midterm Guide: Central Limit Theorem, Confidence Interval, Poisson Distribution

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Standardization theorem: z n( , ), then z x . X n( x=e ( x )= , x=sd ( x )= . Suppose a rs of size n is obtained from a non-normal population with mean and sd . Used for non-normal distributions with size n 30. Law of large numbers (lln): as size n increases, Gamblers fallacy: the belief that the law of large numbers applies in the sr. Suppose a rs of size n is obtained from a normal population with mean unknown and sd known. Then a (1 - )100% ci for is: The margin of error at (1 - )100% confidence is: moe = z /2. Suppose a rs of size n is obtained from a non-normal population with mean and standard deviation (known). If n 30, an approximate (1 )100% con dence interval for is: Suppose a random sample of size n is obtained from a normal population with mean and standard deviation (unknown).

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