a process to ensure the reliability of test results

However, this doesn't happen in practice, and the results are shown in the figure below. Ideally, the two tests should yield the same values, in which case the statistical reliability will be 100%. (Disclaimer: This is just an illustrative example - no test has actually been conducted) Time after injection Depending on various initial conditions, the following table is obtained for the percentage reduction in the blood pressure level in two tests. Reliability can be measured and quantified using a number of methods.Ĭonsider the previous example, where a drug is used that lowers the blood pressure in mice. Simply put, reliability is a measure of consistency. In many cases, you can improve the reliability by taking in more number of tests and subjects.

This means that people will not trust in the abilities of the drug based on the statistical results you have obtained. However, if the reliability is low, this means that the experiment that you have performed is difficult to be reproduced with similar results then the validity of the experiment decreases. The statistical reliability is said to be low if you measure a certain level of control at one point and a significantly different value when you perform the experiment at another time. You would want to do a number of tests and if the results are found to be good in controlling blood pressure, you might want to try it out in humans too. For example, suppose you are studying the effect of a new drug on the blood pressure in mice. This is essential as it builds trust in the statistical analysis and the results obtained. It refers to the ability to reproduce the results again and again as required.

A process to ensure the reliability of test results