Difference Between Validity and Reliability in Research: A Student's Guide!
14 Sep 2022 4954Table Of Contents
- What Is Reliability in Research?
- Importance of Reliability in Research
- How Is Reliability Accessed?
- How Can Reliability in Research Be Ensured?
- What Is Validity in Research?
- Importance of Validity in Research
- How Is Validity Accessed?
- How to Ensure Validity in Research?
- Difference Between Validity and Reliability
- Who Can Provide a Well-Researched Assignment help?
Validity Vs. Reliability: Types & Importance in Quantitative Research!
It is no brainer that an academic paper in quantitative studies revolves around collecting & analyzing numerical data. Students resort to different methods and techniques to gather factual information. Questionnaires, interviews, observations, records, etc. are some methods you must be currently using in your dissertation/thesis too. But, ever wondered what the accuracy & consistency of your chosen method is. Well, this is where the terms 'reliability' & 'validity' comes into the picture. This will bring a lot of questions in your mind like what is the difference between validity and reliability in research, what are their importance in research, to name a few.
The answers to all your questions are contained in this piece of information. Hey, students! Welcome to the blog, which highlights what is validity and reliability in research, their difference, and importance.
What Is Reliability in Research?
The term reliability refers to consistency in general English. In the context of quantitative research, reliability is a quality assessment factor that determines whether the findings will be the same if the research is repeated multiple times under the same conditions. Okay, let us understand it with an example:
“You use a thermometer to measure the temperature of a liquid sample multiple times under the same conditions. The thermometer highlights the same temperature every time. Thus, the results are reliable.”
Furthermore, there are two major aspects of reliability in research. They are-
Stability: This characteristic can be ensured by comparing the results obtained after repeated measurements.
Equivalence: The feature can be gauged by the comparison of results of the same event by two researchers.
Also, one thing to note here is that reliability is most affected by random errors than systematic errors. Before discussing the difference between validity and reliability in quantitative research, here is the significance of reliability in research.
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Importance of Reliability in Research
It plays a vital role in research. For instance, in the case of psychological research, it identifies if the study stands tall on its predicted aims & hypothesis or not. Moreover, if the study comes out to be reliable, then it can be implied to other areas as well. Thus, it is an essential assessment factor in quantitative research. After knowing the importance of reliability in research, now comes the time to analyze how it is assessed.
How Is Reliability Accessed?
Comparing un-identical versions of the same measurement is the best way to assess reliability. There are many statistical methods which are used for estimating consistency. Let us now flashlight on different types of reliability:
- Test-Retest: It assesses the reliability of the measure across time- was the result similar when the measurement was repeated?
Example: A questionnaire based on the economic breakdown is completed by a group of participants. Now, the same questionnaire is repeated after a few days, weeks, or months. If the answers given are the same, then the test-retest reliability is high.
- Interrater: The consistency of a method is assessed across raters or observers- where the findings the same when the same experiments were conducted by different people?
Example: A student project is evaluated by five different examiners based on assessment criteria. The results submitted by the examiners are different; this indicates low inter-rater reliability of the assessment checklist.
- Internal Consistency: It refers to the reliability of the measurement itself- does different parts of the test, which are designed for measuring a similar thing, delivers the same result?
Example: A questionnaire is designed for measuring personality traits. If the result is randomly split into two parts, then a strong relationship between the sets must be present. Else, low internal consistency is indicated.
Professors usually ask the students to prepare a "difference between validity and reliability" PPT. Thus, if you are aware of the different types of assessment tools, then you can covey our message effectively.
How Can Reliability in Research Be Ensured?
Reliability is an important essence that should be considered during the data collection process. While using a method or technique for gathering information, it becomes important to ensure that the findings are stable, reproducible, and precise. Consistency can be achieved by the following:
- Consistent Application of Your Method
Effective planning of your research method is required so that the same steps are carried out in a similar way for each measurement.
- Keep the Research Conditions Standardized
The impact of the external factors can be greatly reduced by keeping the circumstances as consistent as possible. In this way, the variation in the results can be avoided.
After knowing what reliability is in quantitative research and the importance of reliability in research, let us now dig dipper into the concept of validity.
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What Is Validity in Research?
Validity means accuracy in the English language, and therefore, it focuses on the accuracy of a method. In simpler terms, it tells whether the findings really measure to the extent that they were supposed to measure? For a better understanding of what is validity in research, let us take an example:
“Even after keeping the surrounding conditions constant, if the thermometer which you used for testing reliability shows the different temperature of the liquid sample, then the measurements are not valid.”
Moving on further now is the time to discuss the importance of validity as only then we can analyze the individual importance of validity and reliability in research.
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Importance of Validity in Research
The significance of accuracy can be known by the fact that it determines the research questions that solve the purpose of the study. High validity means that the chosen method generates results related to real characteristics, variation, and properties in the physical and social world. Moreover, one thing to keep in mind is that reliability isn't the sole criteria to ensure validity. For instance, if a method is reliable, then it may fail to reflect the actual situation accurately.
How Is Validity Accessed?
Validity is tough to assess than reliability. It is estimated by drawing the comparison between the results and other relevant theory or data. Validity can be estimated via different methods, which are usually split up into different types. Below are the different types of validity.
- Construct: It refers to the adherence of the method with the existing knowledge & theory of the concepts being measured.
Example: A questionnaire-based on mental health can be assessed by evaluating the other traits related to the same concept. A strong correlation will definitely indicate higher construct validity.
- Content: The measurement should cover all the aspects of the concepts being tested. It is also known as face validity.
Example: A test that aims to measure the student's expertise in English contains components related to writing, speaking, and reading, but no listening component. But, the language ability depends heavily on the listening ability, and thus, the method lacks content validity.
- Criterion: It determines whether the measuring instrument performs exactly as the valid measuring parameter related to the concept or not.
Example: A survey to record the political opinions of the people is conducted. If the findings successfully predict the later outcomes, then the survey is considered to have high criterion validity.
How to Ensure Validity in Research?
If you are using ratings or scores to measure fluctuation in something, then it becomes necessary that your findings reflect the real variations accurately. Validity is undoubtedly the earliest stage in the research process when you determine how you will collect the data. Validity can be achieved in the below-mentioned ways:
- Method of Measurement Should Be Chosen Appropriately
Choose the method based on thorough research and existing knowledge. Make sure that the measurement technique should be of high quality and focus on what you wish to know.
- Select the Subjects Using Appropriate Sampling Methods
For valid generalize results, clearly define the audience you are researching (participants belonging to a specific location, age range, etc.). Also, make sure that you have enough participants.
Difference Between Validity and Reliability
The fundamental differences between reliability and validity in research are listed below:
- On the one hand, validity determines accuracy. And on the other hand, reliability reflects consistency.
- The degree to which the measuring instrument gauges is known as validity. Whereas, reliability refers to the degree of reproducibility of the findings.
- In terms of measuring instrument, a valid instrument will always be reliable, but the same is not the case with reverse instrument. A reliable instrument may not be a valid instrument.
- Assessing reliability is easy as compared to assessing validity.
- Reliability is assessed by verifying the consistency of findings across different parts of the test, across time, and across various observers. In contrast, validity is assessed by checking how accurate the findings correspond to the existing theories related to the same concept.
Reading so far, you must have known what is validity and reliability in research. Also, the importance of validity and reliability in research is also known. Moreover, you must have also got the answer to the question- what is the difference between variability and reliability in research?
You are now well-equipped in performing in-depth research for your dissertation/thesis/ However, if you still fail to do the same, then the subsequent section contains the solution.
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