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Reliability and Validity

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Reliability and Validity
Reliability and Validity are important aspects of research in the human services field. Without reliability and validity researchers results would be useless. This paper will define the types of reliability and validity and give examples of each. Examples of a data collection method and data collection instruments used in human services and managerial research will be given. This paper will look into why it is important to ensure that these data collection methods and instruments are both reliable and valid.
Reliability is the consistency of your measurement, or the degree to which an instrument ensures the same way each time it is used under the same condition with the same subjects. In short, it is the repeatability of a measurement. A measure is considered reliable if a person's score on the same test given twice is similar (American Educational Research Association, American psychological Association & National Council on Measurement in Education, 1999).
It is important to remember that reliability is not measured, it is estimated. For example, on a reliable test, a student would be expecting to receive the same grade regardless of when the student completed the assessment or test, when the answer was scored and graded, and who scored the response. On an unreliable examination, a student's grade or score may be different based on factors that are not related to the purpose of the test or survey. There are two ways that reliability is estimated, test/retest and internal consistency. The first implements the measurement of an instrument at two separate times for each subject. The second documents the correlation between the two separate measurements and the third assumes there is no change in the underlying condition of the survey, questionnaire or test.

Validity is one of these criteria. In the most general terms, it shows how well the measure or design does what it purports to do. The measure in question might be a psychological test of some kind, a

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