Why is sample size important in statistics?

Why is sample size important in statistics?

Sample size is crucial because it affects the reliability and validity of statistical results. A larger sample size generally leads to more accurate estimates and reduces the margin of error.

What happens if the sample size is too small?

If the sample size is too small, the results may not be representative of the population, leading to biased conclusions and increased variability.

How do I determine the right sample size for my study?

To determine the right sample size, consider factors like the population size, the desired confidence level, the margin of error, and the expected effect size.

Can you give an example of a study with a small sample size?

Sure! A study on a new medication with only 10 participants may yield unreliable results, as it may not capture the diversity of the larger population.

What tools can I use to calculate sample size?

You can use statistical software like G*Power, online calculators, or formulas based on your study's parameters to calculate sample size.