The correct answer is A. Type I error.
A Type I error is committed when the hypothesis is true but the test rejects it. This means that the test concludes that there is a difference between the two groups when there actually is no difference.
A Type II error is committed when the hypothesis is false but the test fails to reject it. This means that the test concludes that there is no difference between the two groups when there actually is a difference.
Both Type I and Type II errors are undesirable, but Type I errors are generally considered to be more serious because they can lead to false conclusions.
Here is a more detailed explanation of each option:
- Option A: Type I error. A Type I error is committed when the hypothesis is true but the test rejects it. This means that the test concludes that there is a difference between the two groups when there actually is no difference. For example, if a researcher is testing the hypothesis that a new drug is effective, a Type I error would occur if the researcher concluded that the drug is effective when it actually is not.
- Option B: Type II error. A Type II error is committed when the hypothesis is false but the test fails to reject it. This means that the test concludes that there is no difference between the two groups when there actually is a difference. For example, if a researcher is testing the hypothesis that a new drug is effective, a Type II error would occur if the researcher concluded that the drug is not effective when it actually is.
- Option C: Both A and B. Both Type I and Type II errors are undesirable, but Type I errors are generally considered to be more serious because they can lead to false conclusions. For example, if a researcher concludes that a new drug is effective when it actually is not, this could lead to the drug being used by patients when it is not actually effective. This could potentially harm patients.
- Option D: None of these. None of these options are correct.