When conducting research, you will encounter different **types of variables**. These include categorical and nominal variables. You may also come across ordinal and ratio variables. You must decide which type of variable to use for your research. Moreover, it would help to consider how you would analyse these variables.

**Nominal/categorical variables:**

Whether conducting a survey, an experiment, or a research study, categorical and nominal variables are important to your research. These variables are typically measured by a scale and can take different values. Such variables include age, income, province or country of birth, educational level, and housing type. There are two basic types of categorical variables: nominal and ordinal.

Nominal/categorical variables are the most common variables used in research. They are often used in conjunction with quantitative variables. Both variables are useful for research and are important for statistical analysis.

**Ordinal variables:**

Ordinal variables are quantitative data that are categorised in a specific order. They can include numerical values and may not follow a natural progression. For example, ordinal data may include people’s income levels and other characteristics. Ordinal variables are often used in socioeconomic surveys. And can give researchers a rough idea of a population’s socioeconomic status.

Ordinal variables should be displayed properly when displaying data collected from a survey. You can report ordinal data in the form of a frequency distribution table. This table will give researchers an idea of the number of responses for each category.

**Ratio variables:**

Ratio variables are measurements that involve an aspect of time or distance. In statistical analysis, ratio data is useful because You can use it to calculate multiple values. It also allows for multiplication and division. This type of data is commonly used in academic tests and mathematics problems. It is important to understand how to use ratio data in your research.

Ratio data has the same statistical properties as interval data. However, when using ratio data, you will need to make sure that you use parametric tests. These tests are best suited for this type of data, offering deeper insight than non-parametric tests. However, non-parametric tests only take advantage of a subset of ratio data characteristics.

**Intervening variables:**

In studying causal relationships, testing the effect of intervening variables is important. These studies can help researchers to understand prevention and treatment programs better. They can also help to establish the plausibility of causal sequences. Many different types of interventions can be used to test the effect of intervening variables.

The main purpose of an intervening variable is to clarify the relationship between the independent and dependent variables. Sometimes, these variables are referred to as mediator variables or intermediary variables.

**Dependent variables:**

You often have to consider the independent and dependent variables when doing research. In other words, you want to find out what affects the other because both can influence your research. For instance, if you study how bright light attracts moths to a certain location, you will have to look at the independent and dependent variables.

**A dependent variable** can be simple as a student’s test score. Several factors affect a student’s test scores, including the amount of study time, sleep, and hunger. In psychology, you might study how changes in one variable affect another, such as depression. A dependent variable can be an important part of a psychology experiment because it allows researchers to see if there are cause-and-effect relationships.

**Author Bio:**

Carmen Troy is a research-based content writer who works for **Cognizantt**, a globally recognized ** E-Commerce-SEO** and **Research Prospect; a** **Dissertatie schrijven diensten tegen de beste prijzen in het Verenigd Koninkrijk** Mr Carmen holds a PhD degree in mass communication. He loves to express his views on various issues, including education, technology, and more.

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