Variables In The Area Of Quantitative Research
Content Outline
- Introduction
- What are Variables?
- Types of Variables
- A Note on Variables in Qualitative Research
- Summary
Introduction
A variable is a characteristic, or a quantity of a phenomenon that can be measured or classified. As the
name suggests, the values of variables can vary over time or across units. Quantitative research focuses on
explaining the relationship between variables. Therefore, understanding the purpose, operationalization
and measurement of variables is a key part of quantitative research.
What are Variables?
Variables are an essential part of quantitative research. Variables
are characteristics, or a quantity of a phenomenon that is the focus of a research project. Variables can be
measured or categorized, and their values vary across unit, or across time. Gender, hair color, shoe size,
income levels, disease status – all of these are examples of variables. However, variables can also
measure abstract concepts – for example, self-esteem, well-being, sense of religiosity, intelligence, etc.
Some variables are more complex, and may be studied through different dimensions of a particular item
or phenomenon.
For example, in a study on socioeconomic status we may use “income” as our variable or we may use ownership of a permanent housing structure or amount of savings. Another example is a study on academic achievement of 5th graders. Here, we could use “annual exam grade” as the variable denoting academic achievement or “average test grade” (the average of all exams and tests conducted during the year) or “literacy level” to denote academic achievement. Thus, different researchers studying the same topic may choose different variables, depending on the focus of their research. Different researchers may also use different ways of measuring the same concept.
A variable by definition must vary, that is the different participants or units in the study must demonstrate differences in terms of that variable. Gender may be a variable in one study and, therefore, in this study, you would expect to see people of different genders. But if a study was looking only at married women, then all people in the study would be women and so, gender of the woman would not be a variable in that study.
Quantitative research places great emphasis on variables because the main goal of quantitative research is to examine the relationship between two or more variables. Therefore, once the researcher identifies a research topic, the next step is to identify the key variables in the study. The best way to do this is to read studies that are similar to your chosen study. Once you analyze the different types of variables identified by other researchers, you will have a better idea of what variables might work best in your project.
Identifying the most appropriate variables is important for multiple reasons:
For example, in a study on socioeconomic status we may use “income” as our variable or we may use ownership of a permanent housing structure or amount of savings. Another example is a study on academic achievement of 5th graders. Here, we could use “annual exam grade” as the variable denoting academic achievement or “average test grade” (the average of all exams and tests conducted during the year) or “literacy level” to denote academic achievement. Thus, different researchers studying the same topic may choose different variables, depending on the focus of their research. Different researchers may also use different ways of measuring the same concept.
A variable by definition must vary, that is the different participants or units in the study must demonstrate differences in terms of that variable. Gender may be a variable in one study and, therefore, in this study, you would expect to see people of different genders. But if a study was looking only at married women, then all people in the study would be women and so, gender of the woman would not be a variable in that study.
Quantitative research places great emphasis on variables because the main goal of quantitative research is to examine the relationship between two or more variables. Therefore, once the researcher identifies a research topic, the next step is to identify the key variables in the study. The best way to do this is to read studies that are similar to your chosen study. Once you analyze the different types of variables identified by other researchers, you will have a better idea of what variables might work best in your project.
Identifying the most appropriate variables is important for multiple reasons:
- Variables provide focus to the study. So if you pick the wrong ones, the findings of the study may go in a direction that was not expected by you.
- It is also important to focus on the methods and tools for measuring the selected variables. Picking the wrong ones may also take the findings into an unintended direction.
- Variables are also useful when you are searching for other studies (for example in journal articles) that are similar to yours. Thus, the variables can serve as search terms.
Researchers may also find it useful to pretest their choice of variables to make sure they provide the
expected results.
In summary, during your literature review, spend some time analyzing the different types of variables used in the various studies relating to your topic, and how these choices affected the findings of the study. This process will give you some ideas of different variables you could use for your study, and will help you make the most informed choice.
In summary, during your literature review, spend some time analyzing the different types of variables used in the various studies relating to your topic, and how these choices affected the findings of the study. This process will give you some ideas of different variables you could use for your study, and will help you make the most informed choice.
Types of Variables
We use two types of variables in research studies, and you have learned about these in a previous module.
The two types of variables are Independent and Dependent variables. Independent variables are variables
that influence or predict change on Dependent variables. In conducting research studies, researchers
observe how the Dependent variables change as the Independent variable changes. In an experimental
study, the researcher controls or manipulates the Independent variable to see how this affects (or not)
changes in the dependent variable(s). In a study which looks at causal effects, the Independent variable is
a presumed cause whereas the dependent variable is the presumed effect. For instance, in a study which
involves a new blood pressure medication, the new medication or the old medication would be the
Independent variable while the differences in blood pressure before and after receiving medication would
be the Dependent variable
Social work research, however, usually examines research where it is difficult to pinpoint specific causes. It involves research where many things influence a phenomenon. For instance, academic achievement of tribal girls may be influenced by the teacher’s attention, encouragement given by parents to education, whether the child has access to additional tutoring as well as whether a school has a toilet or not. Here we may think of the Dependent variable as something that we are interested in rectifying by altering the Independent variables through our interventions. It is more appropriate to say that the changes in the Independent variable predict changes in the Dependent variable.
Variables are also classified as “discrete and continuous variables, numerical and non numerical variables and so on.
Discrete variables take integer values. For instance, household size is a discrete variable because the number of household members can only be an integer. So one family may have 5 members, while another family can have 8 members. However, household size cannot increase by fractions (which would be a non-integer value), as no household can have 5.5 members. On the other hand, continuous variables can take on any numerical value. Thus, age is a continuous variable because age can be an integer (15 years) but can also take fractional values (15.5 years). There are also intervening variables and extraneous variables in experiments. Intervening variables as the name suggests come between the independent and dependent. They help explain the relationship between the independent and dependent variable better. Intervening variables can be caused by the independent variable and has an impact on the dependent variable. Let us suppose that we are trying to see the effect of high stress levels on the marks of students- Our hypothesis could be: the higher the stress levels, the lower the marks. When conducting the study, we find out that many students do poorly because they are sleepy during the exams. Further investigation reveals that high stress lead to low levels of sleep and that in turn leads to low marks. Here levels of sleep can be considered the intervening variable. Extraneous variables are unwanted or undesirable variables which can have an impact on the outcome of the study. It is important to control these so that they do not influence the course of the research.
Social work research, however, usually examines research where it is difficult to pinpoint specific causes. It involves research where many things influence a phenomenon. For instance, academic achievement of tribal girls may be influenced by the teacher’s attention, encouragement given by parents to education, whether the child has access to additional tutoring as well as whether a school has a toilet or not. Here we may think of the Dependent variable as something that we are interested in rectifying by altering the Independent variables through our interventions. It is more appropriate to say that the changes in the Independent variable predict changes in the Dependent variable.
Variables are also classified as “discrete and continuous variables, numerical and non numerical variables and so on.
Discrete variables take integer values. For instance, household size is a discrete variable because the number of household members can only be an integer. So one family may have 5 members, while another family can have 8 members. However, household size cannot increase by fractions (which would be a non-integer value), as no household can have 5.5 members. On the other hand, continuous variables can take on any numerical value. Thus, age is a continuous variable because age can be an integer (15 years) but can also take fractional values (15.5 years). There are also intervening variables and extraneous variables in experiments. Intervening variables as the name suggests come between the independent and dependent. They help explain the relationship between the independent and dependent variable better. Intervening variables can be caused by the independent variable and has an impact on the dependent variable. Let us suppose that we are trying to see the effect of high stress levels on the marks of students- Our hypothesis could be: the higher the stress levels, the lower the marks. When conducting the study, we find out that many students do poorly because they are sleepy during the exams. Further investigation reveals that high stress lead to low levels of sleep and that in turn leads to low marks. Here levels of sleep can be considered the intervening variable. Extraneous variables are unwanted or undesirable variables which can have an impact on the outcome of the study. It is important to control these so that they do not influence the course of the research.
A Note on Variables in Qualitative Research
We began this unit by saying that variables are integral to Quantitative Research because a researcher
wants to assess or measure the impact of change in one or more variable on another variable. But
qualitative research also sometimes uses the language of quantitative research. It will also refer to
variables, namely characteristics on which people or social units differ. But here the researcher will not
use statistical tests. Instead, they will build a conceptual map that shows the relationship between
variables as initially hypothesized by them or as emerges from the revelations of research participants.
Summary
- A variable is a characteristic or a quantity of a phenomenon that can be measured or classified. The values of variables can change over time or across units.
- Variables are important to quantitative research because this type of research focuses on explaining the relationship between variables.
- Variables play a key role in the selection of the methods and tools in a study, and thus influence the results of the study.
- When choosing variables, the best way is to conduct a literature review, and see what variables have been used in similar studies. Where this is not a possibility, researchers may find it useful to pretest their choice of variables to make sure they provide the expected results. It is also advisable to use multiple variables to measure the same concept – this helps the researchers to identify which variables are the most appropriate fit, and can also help to ensure that the concept being measured is measured completely.
- Variables are of two types – Independent and Dependent variables.
Reference
- Bhardwaj, R. S. (1999). Business Statistics. New Delhi: Excel Books. IGNOU Study Material (2005). EEC-13: Elementary Statistical Methods and Survey Techniques, Block 6.
- Kothari, C.R. (1985). Research Methodology: Methods and Techniques. New Delhi: Wiley Eastern.
- Young, P. V. (1988). Scientific Social Surveys and Research, Prentice Hall of India: New Delhi.
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