Groups selected depending on the extreme scores are not as extreme on subsequent testing. Participants of the first experiment may react differently during the second experiment.Ĭhanges in the instrument’s collaborationĬhange in the research question may give different results instead of the expected results. The results of one test affect the results of another test. The influence on the independent variable due to passage of time.ĭuring a long-term experiment, subjects may feel tired, bored, and hungry. If you feel the increased weight of your experiment participants is due to lack of physical activity, but it was actually due to the consumption of coffee with sugar. Unexpected events during the experiment that are not a part of treatment.
However, it was showing consistent results, but it cannot be considered as reliable. It isn’t easy to interpret the real situation.Įxample: If the weighing scale shows the same result, let’s say 70 kg each time, even if your actual weight is 55 kg, then it means the weighing scale is malfunctioning. Most of the time, validity is difficult to measure even though the process of measurement is reliable. If you get the same response from various participants, it means the validity of the questionnaire and product is high as it has high reliability. Hence you are getting inaccurate or inconsistent results that are not valid.Įxample: Suppose a questionnaire is distributed among a group of people to check the quality of a skincare product and repeated the same questionnaire with many groups. Your weighing machine might be malfunctioning. It means your method had low reliability. In contrast, if a method is not reliable, it’s not valid.Įxample: Your weighing scale shows different results each time you weigh yourself within a day even after handling it carefully, and weighing before and after meals. If a method is reliable, then it’s valid.
If the method of measuring is accurate, then it’ll produce accurate results. If the results are accurate according to the researcher’s situation, explanation, and prediction, then the research is valid. Validity shows how a specific test is suitable for a particular situation. Validity refers to the accuracy of the measurement.
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