What sample size would generally be inadequate for correlational research?

In correlational research, the sample size plays a critical role in determining the reliability and validity of findings. A sample size of 15 is generally considered inadequate for a few important reasons.

Firstly, a small sample size, such as 15, limits the statistical power of the analysis. Statistical power refers to the likelihood that a study will detect an effect when there is an effect to be detected. With too few participants, it becomes challenging to achieve statistically significant results, even if a true correlation exists. This can lead to Type II errors, where researchers fail to identify a relationship that is actually present.

Secondly, smaller samples tend to provide less stable estimates of population parameters. In correlational studies, the intent is to explore the relationship between two or more variables. With only 15 participants, the results may vary widely as a result of random chance, making it difficult to generalize findings to a larger population.

Additionally, smaller samples may not adequately capture the variability of the data. Correlational analysis relies on finding patterns in the data; with a limited number of observations, there may not be enough variability to see clear trends or correlations.

In contrast, larger sample sizes, such as 100, 30, or 50, offer greater reliability