Without this replication of statistically significant results , the experiment and research have not fulfilled all of the requirements of testability. This prerequisite is essential to a hypothesis establishing itself as an accepted scientific truth. For example, if you are performing a time critical experiment, you will be using some type of stopwatch.
Generally, it is reasonable to assume that the instruments are reliable and will keep true and accurate time. However, diligent scientists take measurements many times, to minimize the chances of malfunction and maintain validity and reliability. At the other extreme, any experiment that uses human judgment is always going to come under question. Human judgment can vary wildly between observers , and the same individual may rate things differently depending upon time of day and current mood.
This means that such experiments are more difficult to repeat and are inherently less reliable. Reliability is a necessary ingredient for determining the overall validity of a scientific experiment and enhancing the strength of the results.
Debate between social and pure scientists, concerning reliability, is robust and ongoing. Validity encompasses the entire experimental concept and establishes whether the results obtained meet all of the requirements of the scientific research method. For example, there must have been randomization of the sample groups and appropriate care and diligence shown in the allocation of controls.
Internal validity dictates how an experimental design is structured and encompasses all of the steps of the scientific research method. Even if your results are great, sloppy and inconsistent design will compromise your integrity in the eyes of the scientific community. Internal validity and reliability are at the core of any experimental design. External validity is the process of examining the results and questioning whether there are any other possible causal relationships.
Control groups and randomization will lessen external validity problems but no method can be completely successful. This is why the statistical proofs of a hypothesis called significant , not absolute truth. Any scientific research design only puts forward a possible cause for the studied effect.
There is always the chance that another unknown factor contributed to the results and findings. This extraneous causal relationship may become more apparent, as techniques are refined and honed. If you have constructed your experiment to contain validity and reliability then the scientific community is more likely to accept your findings. Eliminating other potential causal relationships, by using controls and duplicate samples, is the best way to ensure that your results stand up to rigorous questioning.
Check out our quiz-page with tests about:. Martyn Shuttleworth Oct 20, Retrieved Sep 11, from Explorable. It is what goes on inside our heads as researchers. It is where we keep our theories about how the world operates. The second, on the bottom, is the land of observations. It is the real world into which we translate our ideas -- our programs, treatments, measures and observations.
When we conduct research, we are continually flitting back and forth between these two realms, between what we think about the world and what is going on in it. When we are investigating a cause-effect relationship, we have a theory implicit or otherwise of what the cause is the cause construct. For instance, if we are testing a new educational program, we have an idea of what it would look like ideally.
Similarly, on the effect side, we have an idea of what we are ideally trying to affect and measure the effect construct. But each of these, the cause and the effect, has to be translated into real things, into a program or treatment and a measure or observational method. We use the term operationalization to describe the act of translating a construct into its manifestation. In effect, we take our idea and describe it as a series of operations or procedures.
Now, instead of it only being an idea in our minds, it becomes a public entity that anyone can look at and examine for themselves. It is one thing, for instance, for you to say that you would like to measure self-esteem a construct. But when you show a ten-item paper-and-pencil self-esteem measure that you developed for that purpose, others can look at it and understand more clearly what you intend by the term self-esteem.
Now, back to explaining the four validity types. They build on one another, with two of them conclusion and internal referring to the land of observation on the bottom of the figure, one of them construct emphasizing the linkages between the bottom and the top, and the last external being primarily concerned about the range of our theory on the top. Assume that we took these two constructs, the cause construct the WWW site and the effect understanding , and operationalized them -- turned them into realities by constructing the WWW site and a measure of knowledge of the course material.
Here are the four validity types and the question each addresses:. In this study, is there a relationship between the two variables? In the context of the example we're considering, the question might be worded: There are several conclusions or inferences we might draw to answer such a question.
We could, for example, conclude that there is a relationship. We might conclude that there is a positive relationship. We might infer that there is no relationship. We can assess the conclusion validity of each of these conclusions or inferences. Assuming that there is a relationship in this study, is the relationship a causal one? Just because we find that use of the WWW site and knowledge are correlated, we can't necessarily assume that WWW site use causes the knowledge.
Both could, for example, be caused by the same factor. For instance, it may be that wealthier students who have greater resources would be more likely to use have access to a WWW site and would excel on objective tests.
When we want to make a claim that our program or treatment caused the outcomes in our study, we can consider the internal validity of our causal claim. Assuming that there is a causal relationship in this study , can we claim that the program reflected well our construct of the program and that our measure reflected well our idea of the construct of the measure? In simpler terms, did we implement the program we intended to implement and did we measure the outcome we wanted to measure? In yet other terms, did we operationalize well the ideas of the cause and the effect?
When our research is over, we would like to be able to conclude that we did a credible job of operationalizing our constructs -- we can assess the construct validity of this conclusion. Assuming that there is a causal relationship in this study between the constructs of the cause and the effect , can we generalize this effect to other persons, places or times?
We are likely to make some claims that our research findings have implications for other groups and individuals in other settings and at other times. When we do, we can examine the external validity of these claims.
Research validity in surveys relates to the extent at which the survey measures right elements that need to be measured. In simple terms, validity refers to how well an instrument as measures what it .
Issues of research reliability and validity need to be addressed in methodology chapter in a concise manner. Reliability refers to the extent to which the same answers can be obtained using the same instruments more than one time.
In general, VALIDITY is an indication of how sound your research is. More specifically, validity applies to both the design and the methods of your research. More specifically, validity applies to both the design and the methods of your research. Validity encompasses the entire experimental concept and establishes whether the results obtained meet all of the requirements of the scientific research method. For example, there must have been randomization of the sample groups and appropriate care and diligence shown in .
Different methods vary with regard to these two aspects of validity. Experiments, because they tend to be structured and controlled, are often high on internal validity. However, their strength with regard to structure and control, may result in low external validity. Research Methods in Psychology. Chapter 5: Psychological Measurement. Reliability and Validity of Measurement Learning Objectives. Define reliability, including the different types and how they are assessed. Define validity, including the different types and how they are assessed.