What are some common mistakes in determining sample size?

What are some common mistakes in determining sample size?

Common mistakes include using too small a sample size, not considering population variability, and ignoring the desired confidence level.

How does sample size affect the reliability of results?

A larger sample size generally increases the reliability of results by reducing sampling error and providing a more accurate representation of the population.

Can you explain the concept of power in sample size determination?

Sure! Statistical power is the probability of correctly rejecting the null hypothesis when it is false. A larger sample size increases power.

What is the impact of a small sample size on research findings?

A small sample size can lead to unreliable results, increased variability, and a higher chance of Type I and Type II errors.

How can I calculate the appropriate sample size for my study?

You can calculate sample size using formulas that consider the expected effect size, population variance, and desired power level.