What is one solution to overgeneralization in research?

Large samples and replication are essential strategies in research to mitigate the risk of overgeneralization. Overgeneralization occurs when conclusions drawn from a study extend beyond the specific conditions or contexts that were examined. By using larger samples, researchers can better capture the diversity and complexity of the population they are studying, which increases the likelihood that the findings are more representative.

Furthermore, replication involves conducting the same study multiple times, perhaps with different samples or in different contexts. This reinforces the reliability of the results and allows researchers to identify whether the findings can be consistently observed across various conditions. Together, these practices help ensure that conclusions are based on robust evidence rather than limited to a narrow set of data points, thus reducing the risk of making unfounded generalizations about a wider population.