What is the difference between data saturation and statistical power?

• A. Saturation relates to theme emergence; power relates to detecting effects.
• B. They are the same concept.
• C. Saturation is about sample size; power is about data quality.
• D. Saturation refers to the point where no new themes emerge, while statistical power refers to the probability of detecting a true effect given the sample size.

Answer: (D)

Data saturation is about qualitative data collection: you keep gathering interviews or observations until no new themes or insights emerge, indicating that further data are unlikely to add value. Statistical power is about quantitative hypothesis testing: the probability that a study will detect a true effect if one exists, given the sample size, the size of the effect, variability, and the chosen alpha level.

These ideas address different kinds of research design. Saturation concerns content completeness and redundancy in qualitative work, while power concerns a study’s ability to reveal real effects in quantitative work. The correct idea here states both parts clearly: saturation is the point where no new themes emerge, and statistical power is the probability of detecting a true effect with the given data. For example, you might reach saturation after a relatively small number of interviews because themes stabilize, whereas achieving adequate power in a trial might require a larger sample to reliably detect a meaningful difference.