Independent Variable and Dependent Variable

In this blog, we will understand what are the independent variable and dependent variables. How we should identify which one is what? This blog will help you to understand these variables in detail.

Lets go ahead.

Dependent and Independent variables are important for both math and science. If you don’t clearly understand what these two variables are and how they differ from each other, you might struggle in analyzing the plot equation which might end in undesired results. Fortunately, we make learning these concepts easy!

What is Variable?

Before jumping into understanding dependent/independent variables lets understand in brief what is variable. A variable is something you are trying to measure. It can be anything such as objects, events or amount of time, etc. If you are studying how marketing affects sales, then marketing and sales are variable.

There are 2 types of variable in every experiment:

  1. Independent variable: What researches/analyst changes or changes on its own.
  2. Dependent variable: What is being measured.

Lets Read in Detail

Independent variables are variables that are manipulated by analysts or researchers and whose effects are measured and compared. The other name of such a variable is Predictor(s) because it predicts the values of the dependent variable.

Dependent variables are referred to as a type of variable that measured the effect of the independent variable. They are called a predicted variable as well. The dependent variable is completely dependent on the Independent variable. For e.g, in an exam, how much a student is scored depends upon how much he has studied, how much sleep he got before the night of the exam, and what he ate before the exam.   

Variables in Linear Model

In case of linear model, we have the following equation:

y = a + bx, where

y = dependent variable
x = independent variable
b = slope of the line

Other names of such variables

Independent variables are also called ‘regressors’, ‘controlled variable’, ‘manipulated variable’, ‘explanatory variable’, ‘exposure variable’, and/or ‘input variable’.

Dependent variables are also called ‘response variable’, ‘regressand’, ‘measured variable’, ‘observed variable’, ‘responding variable’, ‘explained variable’, ‘outcome variable’, ‘experimental variable’, and/or ‘output variable’.


A few examples can highlight the usage and importance of such variables.

1. If one wants to estimate the cost of living, then the factors such as salary, age, etc are independent variables the cost of living is highly dependent on these factors. Here, the cost of living is dependent variable.

2. In case of poor test scores of a student in an exam, the independent variables can be factors like a student not attending the class, how much sleep a student got before the night of the exam as these will reflect the grades of a student. Here, the dependent variable is a test score.

3. If one wants to compare brands of paper towels, to see which holds the most liquid. The independent variable would be the brand of paper towels. The dependent variable would be the amount of liquid absorbed by the paper towel.

I hope this blog helps you to understand in depth about the dependent/independent variable.

Keep reading and learning!!!!

1 Response

  1. June 18, 2020

    […] Analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called the ‘outcome variable’) and one or more independent […]

Leave a Reply

%d bloggers like this: