How does sample size affect a study?

A sample size plays a critical role in research, particularly regarding the power of the study and the reliability of the results. When a sample size is large enough, it enhances the likelihood of detecting a true effect or association when it exists, which is known as statistical power. A higher power diminishes the probability of Type II errors, where a researcher might fail to identify an existing effect because the sample size was too small.

In addition, a larger sample size generally leads to more reliable results. This reliability comes from reduced variability in the outcome measures and better representation of the population being studied. For instance, a small sample may not adequately capture the diversity of a population, thereby skewing results and leading to less generalizable conclusions. Conversely, a large and appropriately calculated sample size can enhance the confidence researchers have in their findings, ensuring that the conclusions drawn are not simply due to chance.

The options regarding cost, types of analysis, and the notion that sample size has no significant effect on outcomes do not acknowledge the crucial impact that a well-chosen sample size has on the validity of a study's outcomes.