Before attempting to design a research issue, students should be aware of this key question. Variables are notions that may be measured and operationalized in general. There are some notions in the research that the researcher interacts with that are very subjective, such as some concepts regarding a community health program. There will be many perspectives on the initiative, such as whether it will be a success or a complete disaster. The terms "success" and "failure" are very subjective and judgmental terms. If you ask the respondents what they think of the program, they will answer it will be effective, successful, unsuccessful, and beneficial.

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In the research, these and other judgmental phrases cannot be handled scientifically. The reason for this is that their meaning may vary greatly from one individual to the next. Each person's perspective on success or failure may differ significantly. One individual may argue that this community program was successful because it benefitted 50% of the community members, while another may argue that the program should benefit at least 75% of the community members to be considered successful. Subjectivity in research can lead to prejudice. Concepts should be transformed into variables in research to prevent subjectivity. Variables are measurable, making them simple to deal with during the study process.

Variable Definitions in Research

Variables are defined as something that may change, according to basic definitions. Variables are ideas that can be measured using any of the scales available. Variables can have numerical values set to them. There are multiple additional definitions of variables in research, such as variables are those components of the study that change and may be assessed using various scales. These variables are traits or values that may vary; they are more commonly utilized in psychology, although they can also be used in other disciplines.

Variables in research examples

We'll look at two different types of variables in research to see how they affect the study process. Assume you wish to investigate the impact of permanent-press treatments on the durability of cotton cloth. It's an experiment, thus there's an independent variable, a dependent variable, and a control variable in it. The cotton fabric will thus be the dependent variable, while the permanent-press finishes applied to cotton cloth will be the independent variables. There might be a number of additional factors that influence this study, and these factors must be controlled. Extraneous factors, such as the various finishes applied to the cotton cloth, must be controlled in order to see the influence of the independent variable on the dependent variable in the study.


Let's say you wish to investigate the influence of the tsunami on the religious and social life of people living on Sumatra's west coast in Indonesia. It's another cause-and-effect research, this time with people's lives as the dependent variable and tsunami aftereffects as the independent factors. In order to eliminate bias in the study, any other irrelevant variable should be controlled. One thing to keep in mind while doing such research or studies is that the control variable must be managed as well as possible, since it has the potential to derail the entire study. Another option is to include all of the study's other control variables as secondary independent variables. The study grows more empirical and valid as more variables are incorporated, but it also becomes more difficult. It takes longer to measure several factors than it does to investigate the influence of a single variable. Extraneous factors should be included in studies when they are difficult to control.