Type I and Type II errors are two types of errors that may result when making inferences from results calculated on a study sample to the population from which the sample was drawn. They refer to discrepancies between the acceptance or rejection of a null hypothesis, based on sample data, as compared with the acceptance or rejection that reflects the true nature of the population data. Both types of error are inherent in inferential statistics, but they can be minimized through study design and other techniques.

Type I Error

The probability of a Type I error, also known as alpha (α), is the probability of concluding that a difference exists between groups when in truth it does not. Another way to state this is that alpha represents ...

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