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When the probability of one event occurring has no affect on the probability of a second event occurring
Central Limit Theorem
The sampling distribution model of the sample mean and proportion from a random sample is approximately normal for large n regardless of the distribution of the population as long as observations are independent
When we estimate the standard deviation of a sampling distribution using statistics found from the data
Type I Error
Rejecting a null hypothesis when it is true. (Also called a false positive) usually denoted by α
Type II Error
Failing to reject a null hypothesis when it is falso (Also called a false negative) usually denoted by β
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