What does a larger sample size typically increase in research?

A larger sample size in research enhances the power to detect differences or relationships. This increase in power is primarily due to the greater statistical precision achieved when more data points are included. With a larger sample, the estimates of population parameters become more accurate, and the variability of the sample mean decreases. As a result, researchers are more likely to observe significant differences or relationships if they truly exist within the population.

This increased power diminishes the likelihood of Type II errors, which occur when a study fails to identify a true effect. Consequently, a larger sample size allows researchers to make more reliable inferences about the population, thereby strengthening the conclusions drawn from the study.

Other options, such as the potential for biased results, the cost of research, and uniformity of responses, are not inherently improved by increasing sample size. In fact, larger samples could still reflect biases present in the population if not properly randomized, and the cost considerations can increase with size. Uniformity of responses may also be a function of the population's characteristics rather than sample size. Thus, the correct answer is clearly related to the enhancement of statistical power, which is a crucial aspect of research design.