Reliability vs. Validity: Useful Difference between Validity vs. Reliability

Last Updated on December 8, 2023

In an experiment, you need to pay attention to many things. Arguably, two of the most important ones are reliability vs. 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: The Distinctive

Key Takeaways

  • Validity reflects how well a measurement corresponds to actual attributes or differences.
  • Reliability indicates the consistency of measurement results under similar circumstances.

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Reliability vs. Validity: The Definition

What Does Validity Mean?

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.

What Does Reliability Mean?

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.

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.

Comparing Validity and Reliability


We observe that both validity and reliability are measures of assessment quality.

  • Consistency: Both concepts address the need for consistency in research outcomes.
  • Evaluation: We use both to critically assess the tools and methods in research.

Key Differences

Validity and reliability are distinct in several critical ways, as we’ll outline below:

  1. Definition
    • Validity deals with the accuracy of the measurement; it reflects whether the research instrument measures what it’s intended to measure.
    • Reliability is about the consistency of a measurement; a reliable instrument yields the same results under consistent conditions.
  2. Measurement Challenges
    • Assessing validity is more complex than evaluating reliability because it involves illustrating that the instrument measures the intended attribute.
    • Reliability estimation can be accomplished through repeated measurements or by comparing different versions of the same instrument.
  3. Interrelation
    • Validity encompasses reliability; if a method is valid, it’s also reliable. However, a reliable method isn’t necessarily valid.
    • You can think of reliability as a prerequisite for validity, but not vice versa.

Tip to Remember the Differences

When we discuss research, distinguishing between validity and reliability can be tricky. But here’s a simple way to remember:

  • Consistency is key for Reliability: Think of reliability as the repeatability of your measurements. If we’re consistently getting the same results under the same conditions, we’re looking at high reliability.
  • Accuracy is core for Validity: Validity, on the other hand, is concerned with how well a test measures what it’s supposed to. If our test is truly measuring what we intend it to measure, then we’re achieving high validity.

Reliability vs. Validity Examples

Reliability Examples

  • The car’s reliability is its best selling point.
  • We value your reliability as a team member.
  • The study tested the reliability of the new method.
  • Customers trust the brand’s reliability.
  • The machine’s reliability saves on maintenance costs.

Validity Examples

  • The contract’s validity was confirmed by the lawyer.
  • Researchers questioned the validity of the study’s results.
  • The validity of her argument was undeniable.
  • The ticket’s validity expires next month.
  • The experiment tested the validity of the hypothesis.

Frequently Asked Questions

What is the difference between reliability and validity?

We understand reliability as the consistency of a measurement, meaning if we measure the same thing repeatedly, we get similar results each time. On the other hand, validity refers to the accuracy of the measurement, which means the extent to which our method accurately captures what it’s supposed to measure.

Can a measure be reliable but not valid?

Yes, a measure can be reliable without being valid. This occurs when we consistently get the same results, but the results do not accurately reflect what we are trying to measure.

Are reliability and validity important in research?

Absolutely. Both reliability and validity are critical for ensuring that the conclusions we draw from our research are trustworthy. Without them, we can’t be confident in the accuracy or consistency of our research findings.

How do you improve reliability and validity in research?

To improve reliability, we often use clear procedures and repeat measurements. For enhancing validity, we make sure our research design closely aligns with what we aim to measure, and we may use multiple methods to cross-check our findings.

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