Increase in __________ helps increasing statistical power.standard deviationsample sizesignificance levelnone of the above

Break Down the Problem

1. Identify the Options: We need to understand how each option might affect statistical power.
2. Understanding Statistical Power: Statistical power is the probability of rejecting the null hypothesis when it is false.

Relevant Concepts

1. Sample Size: Increasing the sample size generally increases statistical power because larger samples provide more accurate estimates of the population parameters.
2. Significance Level ($\alpha$): Increasing the significance level (e.g., from 0.05 to 0.10) increases power because it makes it easier to reject the null hypothesis.
3. Standard Deviation: Increasing standard deviation tends to decrease statistical power because it increases the variability within the data, making it harder to detect an effect.
4. None of the Above: This option is likely incorrect as at least one of the other options is known to affect power.

Analysis and Detail

1. Sample Size: The relationship is direct; larger samples provide better estimates and more test sensitivity.
2. Significance Level: A higher significance level reduces the threshold needed to reject the null hypothesis, thus increasing power.
3. Standard Deviation: Greater variance makes it harder to identify true effects, thus reducing power.

Verify and Summarize

Among the options provided, increasing the sample size and increasing the significance level both contribute positively to increasing statistical power, while increasing standard deviation has a negative effect.

Final Answer

Sample size helps in increasing statistical power.