What are the difference between Type I and Type II error?

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Accepted Answer

Type I error is rejecting a true null hypothesis, while Type II error is failing to reject a false null hypothesis.

Type I error is also known as a false positive.
Type II error is also known as a false negative.
Type I error occurs when the researcher concludes that there is a significant effect when there is not.
Type II error occurs when the researcher concludes that there is no significant effect when there actually is.
The probability of Type I error is denoted by alpha, while the probability of Type II error is denoted by beta.
Examples of Type I error include convicting an innocent person or rejecting a good drug in clinical trials.
Examples of Type II error include failing to convict a guilty person or approving a bad drug in clinical trials.