An increase in which of the following does not increase power?

Question

BlackTom AI · Accepted Answer

The question asks: An increase in which of the following does not increase power? However, the provided answer_options are missing from the prompt, so I cannot evaluate each choice.

In general, to think about statistical power (the probability of correctly rejecting a false null hypothesis):
- Power tends to increase when the effect size is larger. A bigger true difference makes it easier to detect.
- Power tends to increase with a larger sample size. More data provides more information and reduces standard error.
- Power tends to increase when the significance level (alpha) is higher. For example, moving from 0.01 to 0.05 makes it easier to detect an effect, but at the cost of a greater Type I error risk.
- Power tends to decrease when there is more variability in the outcome measure (greater variance). Higher noise makes it harder to distinguish the effect from random fluctuation.
- The choice between one-tailed and two-tailed tests also affects power: typically, a one-tailed test has more power to detect an effect in the specified direction, assuming the effect is in that direction.

Given these general principles, an option describing an increase in outcome variability (or variance) would typically not increase power; it would usually decrease power. Conversely, increases in effect size, sample size, or alpha would typically increase power, depending on the context and trade-offs.

Because the actual answer_options are missing, I cannot pinpoint which specific option is claimed to not increase power. Please provide the answer_options list so I can assess each choice directly and explain why each would or would not increase power.

An increase in which of the following does not increase power?单项选择题

类似问题

Question 1: With the appropriate hypotheses, when completing a one-sample t test, at 𝛼 = 0.05, the estimated power is 0.547 . You would minimally need a sample size of 43 to achieve the desired acceptable power, when keeping all other conditions the same.

Question 1: With the appropriate hypotheses, when completing a one-sample t test, at α = 0.05, the estimated power is 0.547 . You would minimally need a sample size of 43 to achieve the desired acceptable power, when keeping all other conditions the same.

The practical use of statistical power is that it informs you the researcher:

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