Which option does NOT increase statistical power?

Which option does NOT increase statistical power?

• A. Increase alpha level
• B. Increase sample size
• C. Decrease variability
• D. Use a two-tailed test

Answer: (D)

Power is the probability that a statistical test will reject the null hypothesis when a real effect exists. Increasing the alpha level makes it easier to reject, so power goes up, though it raises the chance of a false positive. Increasing the sample size reduces the standard error, making the test more precise and easier to detect an actual effect, which boosts power. Decreasing variability lowers the noise in the data, improving the signal-to-noise ratio and also increasing power. Using a two-tailed test, however, splits the total alpha into two tails, so each tail has a smaller critical region. With the same effect size and alpha, it becomes harder to reach significance in the expected direction, so power does not increase and is typically reduced compared to a one-tailed test.

Power is the probability that a statistical test will reject the null hypothesis when a real effect exists. Increasing the alpha level makes it easier to reject, so power goes up, though it raises the chance of a false positive. Increasing the sample size reduces the standard error, making the test more precise and easier to detect an actual effect, which boosts power. Decreasing variability lowers the noise in the data, improving the signal-to-noise ratio and also increasing power. Using a two-tailed test, however, splits the total alpha into two tails, so each tail has a smaller critical region. With the same effect size and alpha, it becomes harder to reach significance in the expected direction, so power does not increase and is typically reduced compared to a one-tailed test.