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The difference between validity and reliability is important in research, testing, and statistical analysis. Both are used to determine how well a test measures something, but the two of them tell you different things about your test.
Validity is all about accuracy in your measurements, while reliability determines consistency. Ideally, you want your equipment to be both reliable and valid – or consistent and accurate – be it a thermometer, questionnaire, or scale.
|If a measurement is accurate, then it’s valid.||If a measurement is consistent, then it’s reliable.|
|Validity is essential in all types of testing. If your results are skewed, then your conclusion is likely to be as well.||Reliability is also important. If your instruments for collecting data don’t produce reliable results, you can’t draw any conclusions.|
|Test results can’t be valid if they aren’t reliable. If you keep getting different results from measurements under the same conditions, then it’s neither reliable nor correct.||A tool can have reliable measurements that aren’t valid. If a radar gun isn’t properly calibrated, it may register 50 mph for every car that goes by at 35 mph. It’s reliable, but it isn’t valid.|
|There are three major types of determinations of validity: criterion, content, and construct.||There are four major types of determinations of reliability: test-retest, inter-rater, parallel forms, and internal consistency.|
What is Validity?
Validity is the measure of whether or not your test is accurate. If you have a ten-pound weight and your scale reads it as ten pounds, then it’s valid. Valid test results need not be consistent as long as they’re accurate. If the conditions change – even if you’re unaware of them – then you should get a different measurement.
Hard measurements – such as weight, temperature, and pH – aren’t the only type of measurements that require determining validity. It’s also used in medicine and psychology to determine how useful their surveys and questionnaires are.
For instance, a questionnaire created to determine if a person has a type of illness is valid if the answers predict whether or not the patient suffers from that disease. And if it’s valid, it can be a useful tool for diagnosis.
Of course, validity isn’t quite as simple as that. There are three major types of validity that are referenced in tests.
Criterion Validity. This determines whether or not the test fits the criteria. To put it plainly, it’s whether or not it stacks up to other valid measurements of the same thing.
Construct Validity. Does this test measure what it’s meant to measure? If you want to measure someone’s reading comprehension and instead design a test that is a great indicator of short-term memory, it’s not valid.
Content Validity. Sometimes also called face validity, this measures whether or not the test adequately covers what you’re attempting to measure. For instance, if it’s a test to determine comprehension of a subject in a course, it should cover all the key knowledge learned in the course.
As with most things in studies, validity isn’t a hard measure. Most studies have a sliding scale of validity, and they try to get it as close to the top as reasonably possible, but it’s essentially impossible to have something that’s truly, completely valid.
What is Reliability?
Reliability is the measure of the consistency of your instruments. If a weight put on a scale consistently comes up as ten pounds, then your scale is reliable. It should be noted that the weight in question doesn’t need to weigh ten pounds. If it’s a five-pound weight and the scale is off by five pounds, but it comes up with the same answer every time, it’s still reliable.
As with validity, there are different types of ways to determine reliability.
Test-retest reliability. This determination is exactly what it sounds like. Tests are conducted multiple different times in order to determine the reliability of the results. This is best for something like temperature under similar conditions – something that isn’t going to change.
Parallel forms reliability. With this one, they use different tests that are designed to be equivalent to one another. Sometimes this is also done with split-half reliability, where the test is split into two pieces, and those are compared.
Internal consistency reliability. This is often used in personality tests, where the questions are related to what you’re trying to determine. In personality tests, they will even ask multiple similar questions in order to help determine reliability.
Inter-rater reliability. For this type of reliability, different people run the same study or test, and the results are compared. This is the basis of many serious studies, as someone will run a study, then another person will run a similar or identical study in order to make sure the results can be replicated.
Like validity, reliability isn’t binary in most studies. The goal is to try to get as high a level of reliability as possible. The idea of limited reliability is seen most often in polling – there’s always a listed margin of error. If the margin of error is large enough, it also calls into question the validity.
Validity vs. Reliability FAQ
What is the relationship between validity and reliability?
The relationship between validity and reliability is that they’re both used to determine the efficacy of a test or a study. Validity determines whether or not it’s accurate, while reliability determines whether or not the results are consistent.
What are examples of reliability and validity?
An example of validity is a poll accurately predicting whether or not a candidate will win reelection. An example of reliability is that a poll gets similar results from similar parts of the electorate.
Can something be valid but not reliable?
No, something can’t be valid but not reliable. If your results aren’t reliable, they’re inherently not valid. Validity is accuracy, so if your results aren’t consistent in similar conditions, they can’t possibly be accurate. However, something can be reliable but not valid.
How do you measure reliability and validity?
There are several different ways to measure reliability and validity. For reliability, the best way to do it is to repeat the test multiple times in order to make sure you get the same results. For validity, it’s best to try to compare to other similar results that you know are valid.