Reliability vs. validity! In an experiment, you need to pay attention to many things. Arguably, two of the most important ones are reliability and validity; your experiment needs to be both reliable and valid, in order for it to make sense and provide you with quality results. However, you shouldn’t assume that these two terms mean the same thing because the fact that an experiment is reliable doesn’t necessarily mean that it’s also valid. And how to do you tell the difference?
Reliability vs. Validity
VALIDITY is the extent to which the instruments that are used in the experiment measure exactly what you want them to measure. If an experiment is valid, it means that it has no measurement errors. It also means that the experiment is performed with all the variables taken into consideration, that you covered enough of the subject that you’re testing and that your findings agree with the theoretical assumptions.
RELIABILITY, on the other hand, is the extent to which the outcomes are consistent when the experiment is repeated more than once. In order for the experiment to be reliable, it needs to be performed in a stable environment and without random errors. It’s interesting that if your findings are consistent when the experiment is repeated because you’re constantly making the same error, the experiment will still be thought of as reliable.
- We had doubts about the validity of their argument.
- The reliability of the statistical estimates can be measured.
When to Use Validity vs. Reliability
When it comes to validity, you’re talking about accuracy, i.e. about whether the results that are produced are expected or not. In contrast, reliability has to do with precision, i.e. on how similar are the results when you run the same test over and over again. If the results are always different, they can’t be trusted and, therefore, aren’t reliable.
An experiment that is both valid and reliable is a high school exam. It’s valid because it’s testing the knowledge that the student acquired during the school year, and that’s exactly what it’s designed to do. It’s reliable because, assuming that there’s no way a student can cheat, the exam results will be similar for those students who are passing it in similar conditions, e.g. having been to all the lessons and having studied enough. An example that is reliable but not valid is a broken thermometer. It’s reliable because it does show you the same temperature in the same conditions. However, the temperature isn’t correct because the thermometer is broken: therefore, it isn’t valid.
Reliability vs. Validity Examples
- The reliability of electrical systems has long been both economically and politically essential.
- That will give you total reliability and manners suited to the road.
- In the 1980s, their cars had a bad reputation for reliability.
- This gives much better reliability than a truly absolute method.
- I would question the validity of that assumption.
- The tests have been shown to be of dubious validity.
- Later we shall have cause to doubt its accuracy and validity.
- The available empirical evidence indicates that all three explanations have some validity.
Difference between Reliability vs. Validity | Picture
Reliability vs. Validity: Reliability vs. Validity Difference