Reliability and Validity

These two terms, reliability and validity, are often used interchangeably when they are not related to statistics. When critical readers of statistics use these terms, however, they refer to different properties of the statistical or experimental method.

Reliability is another term for consistency. If one person takes the same personality test several times and always receives the same results, the test is reliable.

A test is valid if it measures what it is supposed to measure. If the results of the personality test claimed that a very shy person was in fact outgoing, the test would be invalid.

Reliability and validity are independent of each other. A measurement maybe valid but not reliable, or reliable but not valid.

Analogy

 Suppose your bathroom scale was reset to read 10 pound lighter. The weight it reads will be reliable (the same every time you step on it) but will not be valid, since it is not reading your actual weight.

Reliability is necessary, but not sufficient for validity.

A test can be reliable without being valid. As example, a test is reliable to be used in testing, but it is not valid because it can only be used to a certain group of students (test about Malaysia’s history is not valid to foreign students). In this case, the test is reliable to evaluate students understanding about the topic. However, it is not valid to foreign students as the items are not generalized to them. This is what it means as a test can be reliable without being valid.

In the other hand, a test cannot be valid without being reliable. An unreliable test cannot be considered valid, because a valid test must be able evaluate what it intended to test. In order to do that, the test must be reliable in the first place. Thus, a valid test must be reliable, but a reliable test does not necessarily a valid test.