Reliability vs. Validity in Research | Types, Differences, and Examples

Validity and reliability in research are two of the most important aspects of a study because no study or research would ever be complete if the results produced or generated therein were to be deemed valid but not reliable or vice-versa. Validity and reliability in research are important as they tell about the organization of studies, data analysis, and utilization of the outcomes. Although they are considered to belong to the same category, they are separate elements of a research study.


The concept of Reliability deals with the dependability of a measure. A reliable instrument gives the same results when the same has been used severally under consistent circumstances. In other words, if an experiment or survey is conducted two or more times, a reliable instrument will come up with results that are consistent giving it strength and dependability.

Types of Reliability

Test-Retest Reliability: This type offers information concerning the fluctuation of the measure in time, to examine whether the measure is consistent in the given period. Test-retest reliability is the measure that says something like this; if a set of people sit an examination, and the same people sit the same examination at a later date, then measure the extent to which the two sets of scores are related. This means is that when one variable is high or low then the other variable is also high or low, this what is referred to as high correlation meaning high reliability.  

Inter-Rater Reliability: This type determines how accurate various assessors or perceivers are when it comes to estimating the identical event.

Internal Consistency Reliability: This type looks at the internal consistency of items in a test in a bid to determine reliability. Indices such as Cronbach’s alpha are employed to determine whether several items, that claim to have the ability to capture the same broad, over-arching concept, arrive at similar results.


Validity in research is defined as the degree of truth in terms of an assessment tool, or simply how well an instrument measures what it set out to measure. Validity in research helps to ascertain that the concept that is inferred from the research study is reliable and relevant.

Types of Validity

Construct Validity: This type establishes whether or not the test targets the particular concept it purports to target. It considers the theoretical foundation of the instrument and consists of the two worth validity assets, namely convergent validity and discriminant validity.

Content Validity: This type asks whether the test captures all the possibilities of the meaning of the concept. Domain specialists usually assess if the test items are good examples of the construct under consideration.

Criterion-Related Validity: This type considers the degree of accuracy used by the instrument in determining an outcome.

Face Validity: This is a more external measure of validity as it aims at asking whether, on the surface, a test seems to be measuring what it set out to measure. However, it doesn’t necessarily mean that such validity is actual, yet it can affect the test’s reception by the users.

Differences and Examples

The key difference between Validity and reliability in research, as stated before is that reliability deals with consistency whereas Validity in research is concerned with accuracy. Thus, a measure can be reliable yet not valid. For instance, a bathroom scale on which one is always on the receiving end of a 5-pound addition is accurate but not precise. On the other hand, a scale showing different readings on different occasions (true one, then five pounds off) is both unreliable and invalid.

Example of Reliability: In a psychological study, high test re-test reliability is obtained if the results of a personality questionnaire do not differ significantly when they are conducted on the same group of people on different occasions.

Example of Validity: In education, a math test purported to measure students’ arithmetic abilities must comprise all the arithmetic subjects (content validity) and ideally has a high correlation with other standard math competence tests (criterion-related validity).

Thus, according to the presented information, it can be stated that both Validity and reliability in research are crucial. It should be noted that Reliability and validity are two fundamental measurement concepts with different focuses; while Types of Reliability stresses the dependability of measurement, the latter addresses the faithfulness of the measuring to the concept under measurement. Both should be critically assessed to guarantee the research results’ reliability and significance.

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