Both of the terms are closely related but they mean different things. In short, reliability refers to the consistency of a measure and validity refers to the accuracy of a measure. This implies that a measurement can be reliable without being valid and on the other hand, if a measurement is valid, it is also reliable.
Let’s see the meanings of the words at first.
What is reliability?
Reliability refers to the degree to which a scale produces consistent results, when repeated measurements are made under the same condition. This means that if the same results come again and again provided that the conditions remain the same, then the measurement is reliable.
For example, if you are weighing the same quantity of wheat on a beam balance over and over again and the result is the same throughout the measurement process, then you can take the weight as a reliable weight. This means that the quantity does not decrease or increase on being measured multiple times.
What is validity?
Validity refers to the extent to which the research instrument measures, what it is intended to measure. A valid instrument is always reliable. In other words, validity is the accuracy of the measurement. If research has high validity, that means it produces results that correspond to real properties, characteristics and variation in the physical or social world. If a method is not reliable, it is probably not valid.
For example, you are measuring your body temperature with a thermometer and it shows a huge difference in the measurement each time. So, you cannot identify the accurate temperature of your body and thus the instrument is not a valid one. Still confused?
Take another example, suppose a person has a certain disease after diagnosis. He goes to several doctors to clarify his disease and each time he gets the same response from different doctors at different diagnostic centres. This indicates that it has high validity as a measurement of medical condition and the person is actually having that disease.
Uses of reliability and validity
Reliability is used in numerous places like data reliability, reliability in computer networking, reliability in semiconductor, reliability in engineering and statistics, and human reliability. It is also used in philosophy and debate.
Reliability in Statistics
Reliability is the overall consistency of a measure.
The different types of reliability are:
Inter-rater reliability which assesses the degree of agreement between two or more raters in their appraisals. Example, a person gets a headache and different doctors’ advice differently.
Test-retest reliability assesses the degree to which test scores are consistent from one test administration to the next.
Inter-method reliability assesses the degree to which test scores are consistent when there is a variation in the methods or instruments used. The other name of inter-method reliability is parallel-forms reliability.
Internal consistency reliability assesses the consistency of results across items within a test.
Reliability in computer networking
In computer networking, a reliable protocol is a communication protocol that notifies the sender whether a particular data has been delivered or not. A reliable service is one that notifies the user if delivery fails, while an unreliable one does not notify the user.
Validity is used in statistics, logic, test validity, theorized psychological construct, drawing inferences in scientific studies, on a scale or test, an outcome, etc.
Validity in Statistics
Validity is a concept or conclusion or measurement which corresponds accurately to the real world. It is the degree to which the tool measures what it claims to measure. In psychometrics, validity has a particular application known as test validity. In logic, validity refers to the property of an argument whereby if the conditions are true then the truth of the conclusion follows. The different types of test validity are
Construct validity which refers to the extent to which operationalizations of a construct measure a construct as defined by a theory.
Content validity evidence involves the degree to which the content of the test matches a content domain associated with the construct.
Criterion validity evidence involves the correlation between the test and a criterion variable taken as representative of the construct. It compares the test with other measures or outcomes already held to be valid.
Important difference between Reliability and Validity in Short
- Reliability refers to the degree of reproducibility of the results of the scale if repeated measurements are done. Validity is the degree to which the scale gauges or what it is designed to gauge.
- When it comes to instruments, you must always remember that a reliable instrument need not be a valid one but a valid instrument is always reliable.
- While evaluating multi-item scale, validity is considered more valuable than reliability.
- Validity focuses on accuracy whereas reliability concentrates on precision.
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