For example, a broken thermometer that gives a different measurement every time it is placed in the same environment under the same conditions is not reliable. This, therefore, means that the results cannot be repeated. If the data (or the instrument) are unreliable, then the data are considered unrelated to the phenomenon or the concept being measured. That is, if you use an instrument or test several times, you should get the same results. Reliability (or precision) refers to consistency. It’s important to consider reliability and validity when you are creating your research design, planning your methods, and writing up your results, especially in quantitative research. Reliability is about the consistency of a measure, and validity is about the accuracy of a measure. They indicate how well a method, technique or test measures something. Reliability and validity are concepts used to evaluate the quality of research.
These two terms are sometimes used interchangeably in research and evaluations.
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