You will soon be introduced to three types of reliability (test-retest reliability, internal consistency, and inter-rater reliability) and four basic kinds of validity (face validity, content validity, criterion validity, and discriminant validity). Researchers strive to use instruments that are both highly reliable and valid. While any valid measure is by necessity reliable, the reverse is not necessarily true. Validity refers to the extent to which a given instrument or tool accurately measures what it’s supposed to measure. While the scale is highly reliable in producing consistent results (e.g., the same amount of cereal poured onto the scale produces the same reading each time), those results are incorrect. If the scale is not properly calibrated, it may consistently under- or overestimate the amount of cereal that’s being measured. To illustrate this concept, consider a kitchen scale that would be used to measure the weight of cereal that you eat in the morning. Unfortunately, being consistent in measurement does not necessarily mean that you have measured something correctly. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways. Reliability refers to the ability to consistently produce a given result. There are two fundamental considerations when developing measured variables: reliability and validity. For example, rigor and control, sample representativeness, clarification, and justification are some ways to improve reliability in qualitative research. IAEA Seibersdorf Historical Images 01210266 There are certain techniques that can help improve reliability in a qualitative research.
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