The difference between the terms ‘validity’ and ‘reliability’ is that validity is the measure of thing in hand that either is correct or incorrect. Whereas reliability is a simpler approach, it has nothing to do with the correctness of the result but what matters is the conclusion obtained by the result.
Validity vs. Reliability
The terms validity and reliability are used in different contexts, but when it comes to statistics, they have a different meaning. Both terms are not related to each other because in statistics if a thing is valid, it is not necessary for it to be reliable. Similarly, if a result is reliable, it is not necessary for it to be valid. For example, if a weight machine is set to give a weight of a maximum hundred kilograms when a thing above hundred kilograms is placed on it, it will still show a hundred kilograms because it cannot read more. This result would be reliable but not valid. Reliability is oriented towards consistency whereas; validity is more about the correctness of results.
What is the Validity?
In statistics, validity is determined as the measure of the preciseness of the results. It counts the accuracy of the results. It is not possible for a human to give 100% accurate results as there always lies and error either human error or instrumentation error. The four types of validity include; Conclusion Validity, conclusion validity is basically the measure that how much the conclusion based on the relationship of variables is reasonable or correct on the base of data given. Whereas the second type of validity is internal validity which determines that the results that are obtained are only under the manipulation of independent variables. No other factor should be involved in the end results. While the third type of validity known as, external validity which means that to which extent a result could be generalized or in other words it is the measure that how much a result is applicable to the other researchers or data. The fourth type known as construct validity could be defined as the degree that a test could measure what it claims. In addition to these validity has many other types too, i.e. Validity evidence, alongside content validity, criterion validity, etc.
What is Reliability?
Reliability refers to the consistency of the result. Let’s start with an example, if a survey is conducted, and it gives the same result for a number of students in the school each year, the test would be reliable because it follows the same procedure that only twenty students are allowed to be in a class and in ten classes there must be two hundred people. The test is reliable but not valid. Because a general statement cannot be applied to all the classes as there might be fewer admissions, students may have left, etc. what matters for reliability is the result only. If a test result is consistent, it would be counted as a reliable result. But if the result doesn’t remain consistent, we may say that or claim that the result is not reliable. It is easier to calculate as follows the same procedure over and over again and hence gets a similar result consistent result again.
- Reliability refers to the consistency of the result whereas the resulting validity measures the preciseness of the result.
- A valid result can or cannot be reliable or while the reliable result can or cannot be valid.
- A result if repeatedly gives the same answer it is said to be reliable while if the result is correct or accurate it is said to be valid.
- There are no such types of reliability all it includes is testing and internal consistency whereas, validity has several types depending upon the degree of preciseness, accuracy and overall generalizing the results.
- Reliability is easier to calculate as it refers only to the consistent results, but validity is difficult to measure as it requires a certain degree of accuracy. As a result to be called accurate.
Validity and reliability thought both terms sound synonymous but they actually are different because of the degree of accuracy and correctness (validity) and consistency of results (reliability). A result could possibly be reliable but not valid and vice versa.