Question

question 8 of 12
why is sample size important?
\bigcirc larger sample size increases the likelihood that the results of a study are not due to random chance.
\bigcirc legitimate scientific studies can be performed using only a large sample size.
\bigcirc statistical significance is best achieved with a small sample size.
\bigcirc researchers will always draw the right conclusions about a set of data if the sample size is large enough.
\bigcirc relationships between variables can be determined only using a large sample size.

Explanation:

Larger samples reduce sampling error, making results more representative of the population and less likely to be caused by random variation. Other options are incorrect: legitimate studies can use small samples (e.g., case studies), small samples hinder statistical significance, large samples don’t guarantee correct conclusions (due to bias/confounding), and variable relationships can be detected with appropriate small samples.

Answer:

Larger sample size increases the likelihood that the results of a study are not due to random chance.