Discussion
Rejecting a null hypothesis when it is true is called :
Answer: A
Rejecting a true null hypothesis is a Type I error.
A Type I error is a false positive: the researcher concludes there is an effect when there is none. Its probability is the significance level, alpha, often set at 0.05.
A Type II error is the reverse, failing to reject a false null hypothesis (a false negative). Sampling error is the chance difference between a sample and the population, and non-sampling errors arise from measurement, response or processing mistakes.
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