The variable can be a number, a name, or anything where the value can change. An example of a variable is temperature. The temperature varies according to other variable and factors. You can measure different temperature inside and outside.
If it is a sunny day, chances are that the temperature will be higher than if it's cloudy. Another thing that can make the temperature change is whether something has been done to manipulate the temperature, like lighting a fire in the chimney.
In research, you typically define variables according to what you're measuring. The independent variable is the variable which the researcher would like to measure the cause , while the dependent variable is the effect or assumed effect , dependent on the independent variable. These variables are often stated in experimental research , in a hypothesis , e. In explorative research methodology, e. They might not be stated because the researcher does not have a clear idea yet on what is really going on.
Confounding variables are variables with a significant effect on the dependent variable that the researcher failed to control or eliminate - sometimes because the researcher is not aware of the effect of the confounding variable.
The key is to identify possible confounding variables and somehow try to eliminate or control them. Operationalization is to take a fuzzy concept conceptual variables , such as ' helping behavior ', and try to measure it by specific observations, e. The selection of the research method is crucial for what conclusions you can make about a phenomenon.
It affects what you can say about the cause and factors influencing the phenomenon. It is also important to choose a research method which is within the limits of what the researcher can do. Time, money, feasibility, ethics and availability to measure the phenomenon correctly are examples of issues constraining the research. Choosing the scientific measurements are also crucial for getting the correct conclusion.
Some measurements might not reflect the real world, because they do not measure the phenomenon as it should. To test a hypothesis , quantitative research uses significance tests to determine which hypothesis is right. The significance test can show whether the null hypothesis is more likely correct than the research hypothesis. Research methodology in a number of areas like social sciences depends heavily on significance tests. A significance test may even drive the research process in a whole new direction, based on the findings.
The t-test also called the Student's T-Test is one of many statistical significance tests, which compares two supposedly equal sets of data to see if they really are alike or not. The t-test helps the researcher conclude whether a hypothesis is supported or not. Drawing a conclusion is based on several factors of the research process, not just because the researcher got the expected result.
A study is considered to have construct validity if the researcher can demonstrate that the variables of interest were properly operationalized. As a researcher, it is important to keep the concept of validity in mind at all times when designing a study. A good researcher will discuss the project design with an advisor or a group of colleagues to help ensure that validity is preserved at every stage of the process. A research project that lacks validity may draw conclusions that are inappropriate or even dangerous if applied to the target population.
For more information about how to ensure the validity of research, please review Research Validity. Conducting Research in Psychology: Measuring the Weight of Smoke, 3rd Edition. Wadsworth Publishing February 27, All Rights Reserved Worldwide.
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?
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.