In the field of research, a variable is an object, idea, or
any other characteristic that can take any value that you are attempting to
measure. Age, blood pressure, height, exam score, sea level, time, and so on
are all variables.

In an experiment, there are two types of variables:
independent variables and dependent variables.

#### Definition of an independent variable

An **independent variable (IV)** is one that stands on its own.
The impact of any other variable has no effect on the value. The independent
variable is manipulated or changed by the researcher in order to assess its
impact on other variables.

Age is an example of an **independent variable** that is not
dependent on any other variable.

#### Definition of dependent variable

Similarly, as the name implies, a **dependent variable (DV)** is
dependent on other variables. The variable is the one being tested in the
experiment. A researcher evaluates the experiment's results to determine how
other variables influence the value of a **dependent variable**.

Take "Test Scores" as an example.

You want to see how studying or sleeping affects a test score.
The **dependent variable** in this example is "test score." The
**independent variable** is "studying" or "sleeping" because
these factors influence how well a student performs on the test.

So, in the experiment, you're attempting to determine
whether and how one variable influences the other. You can change the
**independent variable** (studying time) to see if the **dependent variable** (test
score) changes.

#### Difference between Independent and Dependent Variable

The simplest way to determine which variable in your
experiment is the **Independent Variable** (IV) and which is the **Dependent Variable**
(DV) is to put both variables in the sentence below in the correct order.

"A change in the DV is caused by the IV." It is
impossible for DV to cause any change in IV."

When you change the **Independent Variables** in an experiment,
your goal is to measure the changes in the **Dependent Variables**.

Remember that changes in the **independent variable** have an
effect on the **dependent variable**.

#### Examples of Independent and Dependent Variables

Let's look at some examples of dependent and independent
variables to better understand their characteristics.

How does the amount of sleep affect test results?

1. **Independent Variable**: Sleeping time prior to the exam

2. Test Score is the **Dependent Variable**

What effect does fast food have on blood pressure?

1. **Independent variable**: Fast food consumption

Blood Pressure is the **dependent variable**.

What effect does caffeine have on sleep?

1. **Independent variable**: caffeine consumption

2. **Dependent Variable**: Sleep

#### In Experiment – Independent and Dependent Variables

The independent variable in an experiment is the
characteristic that the researcher manipulates to determine the effect of the
changes on the **dependent variable**.

It is important to note that changing the independent
variable always results in a change in the dependent variable.

For example, you might want to look into the impact of
listening to classical music on math test scores.

To observe changes in test scores, students are divided into
two groups. For two months, students in Group A listened to classical music for
an hour every day. Group B students were not instructed to listen to classical
music.

After two months, students from both groups took a math
test. It was discovered that Group A outperformed Group B.

The **dependent variable** in the experiment was the math exam
test score, and the **independent variable** was exposure to classical music.

While the most common study has one **independent variable** and
one **dependent variable**, it is also possible to have a different level of each
variable in an Experiment.

As a researcher, you may be interested in learning how a
single **Independent Variable** can influence two distinct **dependent variables**.

For example, you might conduct an experiment to learn how
video games affect a teenager's memory and mood. While playing video games is
the **independent variable** in the experiment, the teenager's memory and mood are
the two **dependent variables**.

**Independent variables** can also have different levels. In
some experiments, multiple **independent variables** may be required to examine the
various effects they may have on a single **dependent variable**.

For example, you might be interested in learning how a
healthy diet can aid in weight loss. As a result, you will investigate various
types of healthy diets and their effects on weight.

Different types of diet are your different levels of the
**independent variable** in this case, while weight loss is the outcome that makes
it the **dependent variable**.

Applying two levels of **IV** can reveal whether or not it has
an effect on the **DV**.

Using multiple levels of **IV** can demonstrate how it affects
the outcome of **DV**.

It is not always possible to change the **independent variable**
in experimental research.

For example, you might want to investigate whether age
influences weight gain.

Your **Independent Variable** is your **age**.

Your **dependent variable** is **weight gain**.

You can't change the age of the people you're studying to
figure out how it affects weight gain. So you compare the factors that affected
weight and those that did not.

By comparing the differences in the other factors, you can
learn about a person's weight changes caused by their age.

#### Risks to Be Aware Of

Other variables that may influence the outcome of your
experiment, in addition to dependent and independent variables, must be
considered.

#### Extraneous Variables

Extraneous variables can have an impact on the relationships
between Independent and Dependent variables. Researchers try to identify these
variables so that they can be controlled.

#### Confounding Variables

Confounding variables are those in research that cannot be
controlled. Other variables may exist in non-experimental research that you
have not identified. These variables may have an impact on the outcome.