Researchers also need to consider the reliability of a questionnaire. Will they get similar results if they repeat their questionnaire soon after and conditions have not changed? In our case, if the questionnaire was administered to the same workers soon after the first one, the researchers would expect to find similar levels of depression. Do similar questions give rise to similar answers?
In our example, if two questions are related to amount of sleep, the researchers would expect the responses to be consistent. For example, if two different clinicians administer the depression questionnaire to the same patient, would the resulting scores given by the two be relatively similar?
Although you can never prove reliability or validity conclusively, results will be more accurate if the measures in a study are as reliable and valid as possible.
At Work , Issue 84, Spring Any scientific research design only puts forward a possible cause for the studied effect. There is always the chance that another unknown factor contributed to the results and findings. This extraneous causal relationship may become more apparent, as techniques are refined and honed. If you have constructed your experiment to contain validity and reliability then the scientific community is more likely to accept your findings.
Eliminating other potential causal relationships, by using controls and duplicate samples, is the best way to ensure that your results stand up to rigorous questioning. Check out our quiz-page with tests about:. Martyn Shuttleworth Oct 20, Retrieved Sep 11, from Explorable. The text in this article is licensed under the Creative Commons-License Attribution 4.
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Don't have time for it all now? No problem, save it as a course and come back to it later. Martyn Shuttleworth K reads. Share this page on your website: This article is a part of the guide: Select from one of the other courses available: Don't miss these related articles:. The test and retest is quite easy. You simply test an idea twice, test 1 and test 2. It must be measured twice in different times, then compare the similarities of the results of the two tests. Then, if the results of the two tests are the same, it means that certain measurement is reliable.
The next way in estimating reliability is internal consistency. This can be done by questioning. Make different sets of question that can measure the same factor.
Let this be answered by different people or different groups. And even if different people answered these different questions, but still came out with the right thought, then it must be reliable. This is the definition of reliability. Now to differentiate it with validity, it is best to define validity as well. In this way, the confusion between the two terms may be fixed.
Education Research and Perspectives, Vol, No.1 Validity and Reliability in Social Science Research Ellen A. Drost California State University, Los Angeles.
When we look at reliability and validity in this way, we see that, rather than being distinct, they actually form a continuum. On one end is the situation where the concepts and methods of measurement are the same (reliability) and on the other is the situation where concepts and methods of measurement are different (very discriminant validity).
Reliability and Validity. In order for research data to be of value and of use, they must be both reliable and valid.. Reliability. Reliability is a necessary ingredient for determining the overall validity of a scientific experiment and enhancing the strength of the results. Debate between social and pure scientists, concerning reliability, is robust and ongoing.
Issues of research reliability and validity need to be addressed in methodology chapter in a concise manner. Reliability refers to the extent to which the same answers can be obtained using the same instruments more than one time. In simple terms, if your research is associated with high levels of. Reliability and validity seem to be synonymous, but they do not mean the same thing. They are actually different things, different terms when they are explained in a technical manner. These terms are often used on scholastic outputs such as thesis studies, term papers, research papers, and the likes.