What are the 4 Types of Variables Used in Research?

In the field of statistics, there are four basic types of variables. They are Nominal, categorical, Exogenous, and Independent. Understanding them will help you create a good research study. Here are a few examples:

Nominal variable:

A nominal variable is quantitative data presented as a percentage or proportion. For example, if the population of A. Vulgare is divided into males and females then the balance of males is 52.3%, while the proportion of females is 62.1%. To collect data from this type of study, you need to determine the goal of the research. By defining the purpose of your study, you can formulate guiding questions and answer them. This will also help you choose the most appropriate measurement method.

Consider the structure:

To use a nominal variable in research, you must consider its properties. First, consider its structure. It can be a visualizevisualized chart or a bar graph. Pie charts show percentages, while bar graphs display amounts of variables on a numbered graph. Both types of graphs make it easy for you to analyze. Nominal variables may be grouped into groups based on their types and values.

Categorical variable:

A categorical variable is a variable that has multiple possible outcomes. In research, categorical variables may be discrete or continuous. In the study, categorical variables may also be ordinal or nominal. A researcher can use either type of a variable when comparing two groups. However, it is important to note that a categorical variable has problems. Fortunately, there are several ways to deal with them.

Stores one distinct value:

A definite type of variable that stores one distinct value for each respondent. It is usually based on a question that includes predefined categories, such as "yes" or "no," "blue" or"read," or a more complex set of classes. You can also use categorical variables to represent types of data that can be categorizcategorizedg into groups. Some examples include a person's race, sex, educational level, age, or political affiliation.

Exogenous variable:

An exogenous variable is a variable that originates outside of the system. For example, the state of a country or its agrarian structure may be an exogenous variable. Likewise, a rise in one factor can cause a decrease in another. An exogenous variable can be a confounding factor, which will affect the results of the experiment. That is why it is essential to conduct controlled experiments.

Independent variable:

In statistics, an independent variable is a factor that does not depend on a dependent one. The difference between a dependent and an independent variable is that an independent variable is manipulated directly by researchers while the other variables influence a dependent variable. Independent variables focus on causes and effects. They start with an impact and move up the causal chain to find its cause.

The independent variable in a research study is the change or factor that affects the dependent variable. The dependent variable is the outcome of the changes in the independent variable. When a scientist is evaluating an experiment, they are comparing the effect of one variable to another. Often, these changes are related. For example, in a research study, the amount of light in the room affects the growth of a moth. A scientist will measure the response of the moth to different light levels.

Author Bio:

Carmen Troy is a research-based content writer, who works for Cognizantt, a globally recognized professional SEO service and Research Prospect; an 论文和论文写作服务 Mr. Carmen holds a PhD degree in mass communication. He loves to express his views on various issues, including education, technology, and more.