In research, variables are used to measure effects. There are two types of variables: dependent and independent. A dependent variable is a factor that is dependent on the independent variable. These two types are different but are used together. This article discusses the different **types of variable in research**. It will also explain their functions.

**Nominal:**

Nominal data can be analyzed using non-parametric statistical tests. One common type of test is the Chi-square goodness of fit test, which evaluates the fit of one nominal variable to a given set of data. Another type of statistical test is the Chi-square test of independence, which analyzes the relationship between two nominal variables.

**Nominal variables are used in human subjects research:**

Nominal variables are often used in human subjects research. Some examples include race, nationality, biological sex, and marital status. These variables are often referred to as “demographic traits.” Another type of nominal variable is the type of cancer a person has, which can be classified by its organ. In addition, people may have different brand preferences, or different types of stars.

Nominal variables are names that do not have a natural order. For example, if you want to analyze the gender of a person, you might use a questionnaire that asks if the person owns a Macbook. In this way, you can group the information by this **variable and see the differences**.

**Ordinal:**

Ordinal variables in research examples refer to data that have been classified or ranked. They can be used for a variety of reasons, including comparing two things in terms of their relative importance in a certain context. This kind of data can also be used to compare the different stages of a disease or an individual’s pain level.

**Statistical study:**

In a statistical study, ordinal variables are usually used to compare the differences between two groups or categories. Ordinal variables are also useful when analyzing data for socioeconomic studies. For example, an ordinal variable could be used to compare the performance of students in terms of their behaviour. Usually, these results are displayed in the form of a ranking table, with information categorized by number of students, behaviour, and other factors.

Ordinal variables can also be used to identify trends and patterns. For example, a correlation study might find that high values of one variable are correlated with low values of the other. An analysis of this type of data would also be able to uncover the direction in which the relationship exists.

**Interval:**

Intervals are commonly used in statistical research. This type of data is useful in many types of studies, including IQ testing, grading exams, and applying credit ratings. They also provide a way to measure probability. Researchers can classify interval data into two types: descriptive and inferential. Descriptive statistics summarize characteristics of a dataset, while inferential statistics make comparisons between samples and draw conclusions.

One of the most common types of data, interval data can be collected using a survey. Using survey tools that allow for a range of values, interval data is easily captured and can give rich insights into the results.

**Ratio:**

When analyzing data, you need to take into account the spread of the ratio variables you’re using. A normal distribution is ideal. Parametric tests are more powerful than non-parametric tests and will provide deeper insight into your data. You should also use parametric tests whenever possible, as they will capture the full range of ratio dataset characteristics.

**Ratio variables have all the properties of interval variables:**

Ratio variables have all the properties of interval variables, with the added benefit of having a true zero value. This means that you can multiply, divide, and square root a value with a true zero value. Some examples of ratio variables include length, weight, and pulse. Using ratios in your research will allow you to compare the past with the present.

**Ratio variables are used in scientific studies:**

Ratio variables are used in all kinds of scientific studies. These types of scales are useful in many ways, including statistical analysis. One way to use ratios in your research is to use them for chi-square calculations.

**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.