## What Is A Variable?

From the name, an idea can be obtained about a variable or about the definition of a variable. A variable is a quantity or a kind of measurement. It does not have a fixed value or it keeps on taking different kinds of values. Therefore, as a definition of a variable, it may be said that A variable is a quantity that may change within the context of a mathematical problem or experiment. Typically, we use a single letter to represent a variable. Though a variable doesn’t hold a constant value, it has a pattern of values.

## Types of variables:

Mainly, there are six common types of variables. These are explained as follows.

### Introduction:

There are different kinds of variables to study. But among these, they can be divided into six different and major parts. These are given and discussed below.

### Dependent variable:

A dependent variable is a special kind of variable. This kind of variable is used in regression analysis. From the name, it can be understood that a dependent variable is a kind of variable whose values depend upon the values of the other variables. Its value will be changing depending on the values of some other variables.

### Independent variable:

Independent variable is a special kind of variable too. This kind of variable is also used in regression analysis. From the name, if this variable, it can be said that the value of this kind of variable does not depend on the values of the other kinds of variables. But this variable has an impact on the dependent variable. This means in a regression model, the independent variable will be effecting the values of the dependent variable in a model, that is the values of a dependent variable will be changing according to the values of the independent variable in the regression model. Therefore, it may be said that this kind of variable is of the greatest importance.

### Intervening variable:

The intervening variable is also a special kind of variable. This variable does not exist in real life. This variable is only a kind of hypothetical variable. This kind of variable is used in defining the relationship between the independent and the dependent variable which are in a regression model. This kind of variable is not a real variable or a real thing. These variables are used only to interpret any kind of statistical relationships and any kind of observed fact.

### Moderator variable:

The cause-effect relationship between the variables is really important to look into. Moderator variables are the kind of variables that affect the relationship or the direction of the relationship between the two variables or more variables under study. Basically, as a whole, it may be said that moderator variables affect the relationship among the dependent and the independent variables.

### Control variable:

A *control variable* is what is kept the same throughout the experiment, and it is not of primary concern in the experimental outcome. Any change in a *control variable* in an experiment would invalidate the correlation of dependent *variables* (DV) to the *independent variable* (IV), thus skewing the results.

### Extraneous variable:

Extraneous variables are those kinds of variables that are not really independent variables but these variables could affect the results of the experiments of the model under study. It can also be said that this is the manipulation of the independent variables which have effects on the dependent variables under a model.

## Types of data: Quantitative vs categorical variables:

### Quantitative data:

Quantitative data is a kind of data which associates with numerical information. Here, this kind of data or variable is counted or measured with numerical counts, that is, each data point does have a specific value in the data set. In statistical analysis, this kind of data is of greater use.

### Categorical data:

Categorical data is a special kind of data. This kind of data is used to represent the attributes. In the representation of this kind of data, the whole data set is divided into several sections and then some numbers are added to assign to measure the attributes.

## Parts of the experiment: Independent vs dependent variables:

### What Is Dependent variable:

A dependent variable is a special kind of variable. This kind of variable is used in regression analysis. From the name, it can be understood that a dependent variable is a kind of variable whose values depend upon the values of the other variables. Its value will be changing depending on the values of some other variables.

### What Is an Independent variable:

Independent variable is a special kind of variable too. This kind of variable is also used in regression analysis. From the name, if this variable, it can be said that the value of this kind of variable does not depend on the values of the other kinds of variables. But this variable has an impact on the dependent variable. This means in a regression model, the independent variable will be effecting the values of the dependent variable in a model, that is the values of an dependent variable will be changing according to the values of the independent variable in the regression model. Therefore, it may be said that this kind of variable is of greatest importance.

## FAQs Related To Variables:

#### Q. 1. How categorical data is used?

Ans. It is known that categorical data is used to represent different kinds of attributes. Attributes are those kinds of measurement that can not be represented numerically. This is a part of qualitative data. Like, if a certain population is divided according to the hair color, then this will be studied by using categorical variables. For instance, if the population is divided by the hair colors black, brown, grey, and blonde, then some numbers like 1,2,3,4 will be assigned to each kind of hair color and the number of the people who are associated with the different kinds of hair color will be represented by a frequency table. This is how categorical variables are represented.

#### Q. 2. What kinds of variables studied here are of greater importance?

Ans: Each kind of variable has its own significance in its own field of use. Independent and dependent variables are important in building a regression model and studying the effects and the relationship between the variables under study. Again categorical variables and quantitative variables are the variables that may be used in representations. The other variables like control variables, moderator variables, and the others are also somehow associated with the dependent and independent variables, and this helps to analyze and to represent the variables in the study. Therefore, it may be said that all kinds of variables are of different kinds of importance.

#### Q. 3. Write and explain two different kinds of data.

Ans: Data is the main parameter to analyze anything, to represent anything. Now data will not be numeric all the time. Based on the types and characteristics of data, data can be divided in two major parts. These are qualitative data and quantitative data. Qualitative data is used to measure or to represent the attributes, that is the variables that may not be calculated or represented numerically because they are qualities. As an example, it can be said that if the population is divided by the hair colors black, brown, grey, and blonde, then some numbers like 1,2,3,4 will be assigned to each kind of hair color and the number of the people who are associated with the different kinds of hair color will be represented by a frequency table. For this case, categorical variables will be needed. Quantitative data are the kind of data that may be represented numerically. Therefore it may be said that all the numerical data are under the section of quantitative data.

#### Q.4. How are dependent and independent variables used?

Ans: Independent and dependent variables are the terms that are associated with the study of regression analysis. Regression analysis is a kind of study where cause-effect relationship among the dependent and independent variables is studied. Independent variables and dependent variables are the main objectives of any kind of regression model. The values of the dependent variables under study is evaluated with the help of the independent variables and also the value of the intercept part. Therefore, above all, it may be said that by the usage of independent and dependent variables in a regression model, it can be measured how the dependent variable is being changed with the change of the values of the independent variables.

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