Difference Between Reliability and Validity

Reliability vs Validity
 

When taking measurements especially in scientific studies we have to ensure the precision of the data. If the data are not précised, then the outcome or the conclusion we make from those data aren’t going to be valid. In order to increase the precision of the measurements, we use different tactics. One is to increase the number of data, so that the error will be minimized. In other words, this is known as increasing sample size. Another way is to use calibrated equipments and equipments with less error. Not only the equipment but the person who takes the measurement is also of very importance. Normally an expert would take the measurements. Also to minimize the error of the experimenter we can use several people and repeat the same experiment few times. Reliability and validity are two important aspects of precision and accuracy.

Reliability

Reliability refers to the reproducibility of a measurement. This measures the consistency of the measurements taken from an instrument or an experimenter. We can draw a conclusion about the reliability by taking the same measurement using the same conditions few times. If similar outcome is resulted at all the attempts, then the measurements are reliable. If reliability is poor, it is hard to track the changes in the measurements. Also, poor reliability degrades the level of precision.

Retest reliability method can be applied to measure the reliability. Here, a variable of the same subject is measured twice or more to check the reproducibility. Change in the mean, typical error, and retest correlation are important components of retest reliability. When the difference between the means of two tests is considered, the change in the mean can be calculated. Retest correlation is also another way to quantify reliability. When the test and retest values of an experiment is plotted, if the values are closer to a straight line then the reliability is high.

Validity

Validity refers to the similarity between the experiment value and the true value. For example, the weight of 1 mole of carbon should be 12g, but when we are measuring it could take different values depending on the instrument, person who is measuring, sample condition, external environmental conditions etc. However, if the weight comes very closer to 12g, then the measurement is valid. So validity can be quantified by comparing the measurements with the true values or with values that are very closer to the true value. Poor validity in measurements degrades our ability to characterize relationships and draw true conclusions about variables.

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