Question

How do the significance level, power, effect size, and standard deviation influence the sample size?

Answer 1

1)Significance level to sample size:-

Some researchers choose to increase their sample size if they have an effect which is almost within significance level.

Higher sample size allows the researcher to increase the significance level of the findings, since the confidence of the result are likely to increase with a higher sample size.

2) Power to sample size :-

The price of this increased power is that as α goes up, so does the probability of a Type I error should the null hypothesis in fact be true.

The sample size n. As n increases, so does the power of the significance test. This is because a larger sample size narrows the distribution of the test statistic.

3) effect size to sample size :

This is the estimated difference between the groups that we observe in our sample. To detect a difference with a specified power, a smaller effect size will require a larger sample size.

4) standard deviation to sample size :-

The population mean of the distribution of sample means is the same as the population mean of the distribution being sampled from.

Thus as the sample size increases, the standard deviation of the means decreases; and as the sample sizedecreases, the standard deviation of the sample means increases.