Types of Errors in Hypothesis Testing

Type I Error

• Rejecting a true null hypothesis.
• Also known as a false positive.
• Probability of this error is denoted by alpha (\alpha), the level of significance.
• The researcher is responsible for this error.

Type II Error

• Accepting a false null hypothesis.
• Probability of this error is denoted by beta (\beta).
• Depends on sample size and population variance.
• Considered a less serious problem.

Power of the Test

• The probability of rejecting a false null hypothesis is 1 - \beta.
• Researchers aim to maximize power, often by increasing the sample size.

Examples

• Type I Error: Rejecting a true null hypothesis. (Example: Thinking a girl doesn't like you when she actually does, and missing a chance).
• Type II Error: Accepting a false null hypothesis. (Example: Thinking a girl likes you when she doesn't, leading to awkwardness, but not a major issue).