The use of a variable is very common in research. This is because it plays a major role in quantitative research projects. For all beginners, it is somehow difficult to manage the right use of a variable in quantitative research. But if you spend some time on it, this aspect would not seem difficult. For this to happen, you need to work on the relevant concept. You must also have clarity of all the terms related to research variables.
In general, the concept of research variable is termed for something that changes. Or it can also be a factor that does not have only one value. But one that covers multiple values. The name of the variable was designed as per its functionality to change. It is not specified for a particular task or data. Instead, it covers the demographic information as a whole, like income, status, height, and weight. Also, it covers temperature, anxiety level, and all such things. You can see each category vary from person to person. All humans have different heights and different colours. Similarly, we all have different demographics and other details. The other details include nationality, food, language, and fashion.
Variables and their attributes
You can sort out some values in broader terms, like blood groups in all variables.
It has a specified classification of groups like A, B, AB, and O. You cannot go beyond these classifications. Here, A, B, AB, and O are the attributes of blood groups. The same is the case with gender. It can be either male or female. There is no third category for this. Here male and female are the attributes of gender. And gender is a variable.
Types of Research Variables
Many research variables are available to a researcher. From a broader perspective, it is classified into two categories that are as follows;
- Independent Variable
- Dependent Variable
Let’s discuss each variable in detail and how you can represent it.
Independent research variable has a worth of precursor. Suppose your independent variable is active. In this case, it is easy to evaluate the values. And it becomes easy to measure the effects of active research variables on other ones. For example, you have anxiety. Here you can see how anxiety can be affected by another variable. Or how anxiety affects the other variable. Here you can also measure anxiety by comparing it with medicine. You need to see how medicine reduces the pain of anxiety and to what extent it brings forth any side effects. Within this context, the level of anxiety plays the role of an active variable.
Same as in quantitative research, some common independent variables used in dissertation writing and academic research papers are as follows;
- Rate of fluid flow
These variables are highly used within both mathematical and statistical modelling. You can also see its major role in the domain of experimental sciences.
All variables that are affected by independent variables are termed dependent variables. If we discuss the same example of anxiety level, here, you’ll have a dependent variable in the form of pain reduction. The rate of pain reduction or its increase depends on the anxiety level. The higher the anxiety level is, the more the pain will be. As the anxiety level decreases, the level of pain also decreases. So you can see how dependent variables depend on independent variables.
In statistical terms, the dependent research variable is termed a repressor. The use of a dependent variable is also common in mathematical and statistical modelling. And you can see its use in experimental sciences too.
Examples of Dependent and Independent Variables
Let’s highlight how a research question covers the dependent and independent variables through the following examples;
Question No 1:
How can potatoes grow fast? In which of the following condition does this vegetable show the fastest growth?
- Fluorescent light
- Incandescent light
- Natural light
Here your independent research variable is the type of light. And the dependent variable is the rate of growth of the potato. The growth rate is dependent on the light. You have to see how much growth is affected by each type of light.
Question No 2:
What can be the effects of soda on a person’s sugar levels? How much does diet soda affect one’s health? And how much does regular soda affect sugar levels in the human body?
Here soda is a variable, and the following are its attributes;
- Regular soda
- Diet soda
Your independent variable is the type of soda. And here, the dependent research variable is the rate of increase or decrease of sugar level. The changing rate is dependent on the soda type. You have to see how much change is observed according to each type of soda.
Question No 3:
How much screen time affects your sleep?
Here your screen time includes the use of the following devices;
- Mobile phone
Your independent variable is how long your screen time before you sleep is. There are two dependent variables within this context. The first dependent research variable is the hours of sleep that you take. And the second dependent variable is how good or bad your sleep is. Both research variables are dependent on screen time. The more your screen time is, the less will be your sleeping hours. Similarly, you would not ensure good sleep with more screen time.
Question No 4:
How much salt can a plant bear in water?
In this research question, you have to see how much salt plants are taking through the water. Also, you have to note down how long those plants are surviving. In the same way, you are supposed to collect information about plant growth and the rate of plant sagging. To find the best relation between these variables, you have to categorise them into a dependent or independent research variable category. Here the quantity of salt plays the role of an independent variable. Whereas the following variables work as dependent ones;
- The growth rate of plant.
- Rate of sagging.
- Survival time of plants.
Both dependent and independent research variables are important in the research process. By finding a logical relation between these variables, you can have a valuable conclusion. If either one is missing, you cannot proceed further until you find it. This is because, with a missing research variable, you won’t’ be able to formulate the hypothesis.