Reliability and validity are two concepts that are important for defining and measuring bias and distortion. Outside of statistical research, reliability and validity are used interchangeably.
“Validity” encompasses the entire experimental concept and establishes whether the results obtained meet all of the requirements of the scientific research method. For example, there must have been randomization of the sample groups and appropriate care and diligence shown in the allocation of controls. Internal validity dictates how an experimental design is structured and encompasses all of the steps of the scientific research method.
Even if your results are great, sloppy and inconsistent design will compromise your integrity in the eyes of the scientific community. Internal validity and reliability are at the core of any experimental design.
Innovative validity is the process of examining the results and questioning whether there are any other possible causal relationships.
Reliability: The idea behind reliability is that any significant results must be more than a one-off finding and be inherently repeatable.
Other researchers must be able to perform exactly the same experiment, under the same conditions and generate the same results. This will reinforce the findings and ensure that the wider scientific community will accept the hypothesis.
Without this replication of statistically significant results, the experiment and research have not fulfilled the entire requirement of testability. This prerequisite is essential to a hypothesis establishing itself as an accepted scientific truth.
For example, if you are performing a time-critical experiment, you will be using some type of stopwatch. Generally, it is reasonable to assume that the instruments are reliable and will keep true and accurate time. However, diligent scientists take measurements many times, to minimize the chances of malfunction and validity and reliability.
