Zuverlässigkeit und Gültigkeit

In a scientific setting, suppose a researcher wants to create a test to measure the compatibility of potential partners on an online dating website. They must consider two important factors to generate successful outcomes.

One is reliability, which refers to the ability of a test—or other research instrument—to provide consistent, and thus, reproducible, results under similar circumstances.

In this context, the compatibility test would be considered reliable if the same people take the test twice and perform similarly each time. This situation is also known as test-retest reliability.

However, getting consistent results does not ensure that a test is accurate. Now, the second factor, validity—the extent to which a test accurately measures or predicts what it set out to measure—must be reflected.

Will they actually enjoy spending time together on a date?

If the pair scored low in dating compatibility and still went out to dinner together, perhaps they had a miserable time. In this case, the test did have high predictive validity—it forecasted the behavior.

In the end, researchers strive for reproducibility and accuracy: here, the test is successful if other incompatible couples cont