The types of variables commonly used in statistics are quantitative variables, qualitative variables, independent variables, and dependent variables.

## Quantitative variables

All variables that can be expressed numerically are called quantitative variables. Some examples of quantitative variables are given below.

• Size of basketball players in the United States.
• Income of all football players in Great Britain.
• Number of televisions in Australia.
• Number of train tickets sold in 2005.
• Weight of all newborns.

Quantitative variables can be either discreet or continuously

The difference between a discrete variable and a continuous variable is simple.

If you can count something just the numbers 1, 2, 3, 4, 5, …., the thing is a Discrete variable.

For example, how many cars do you own?

You either own 1, 2, 3, 4, and so on. There is no way to own 1 car plus 1/2 car or 1.5 car.

How many children are in the classroom? It could be 25, 20, or 10 in the classroom. However, it doesn’t make sense to say 20.5 children.

As you can see, a discrete variable cannot be broken down into fractions.

From this explanation, you can see that the quantitative variables above give rise to the following discrete variables.

• Number of televisions owned.
• Number of train tickets sold in 2005.

A continuous variable though fractions and you could have can not to use just the numbers 1, 2, 3, 4, 5, 6, …. to find the variable.

For example, if I ask your age, you might say, “I’m 50 years old.”

However, if I ask you the same question 6 months later, say 50 years and 6 months or 50.5 years old.

Since 6 months or 0.5 years is a fraction of 1 year, the variable is continuous.

In general, the word “number” does not apply to a continuous variable. You never hear people say, “Count your height,” “Count your weight,” etc.

Instead, you can say, “Measure your height,” “Measure your weight,” etc.

The word steady probably came from the fact that the variable can still take intermediate values ​​between two consecutive whole numbers.

For example, between 2 and 3 there are many intermediate values ​​such as 2.5, 2.33, 2.4447, 2.4, 2.00047, and millions of other intermediate values.

Of the quantitative variables above, the discrete variables are as follows.

• Size of basketball players in the United States.
• Income of all football players in Great Britain.
• Weight of all newborns.

## Qualitative variables

A qualitative variable, also called a categorical variable, cannot be expressed with a numerical value. The variable can be observed. We can’t count or measure it.

For example, the gender of college graduates is a qualitative variable.

Other examples of qualitative variables are shown below.

• Hair color of basketball players.
• Types of smells in 5 different cities.
• Marital status of people.

## Independent versus dependent variable

An independent variable can be edited to change its values. A dependent variable cannot choose its values.

The value of the dependent variable always depends on the values ​​that the independent variable takes.

For example, income is an independent variable (a continuous independent variable) and Number of cars bought is a dependent variable (dependent discrete variable).

You can manipulate your income in such a way that it may change by working more or less or working hard to become a doctor or CEO.

However, the number of cars you can own depends on your income.

As your income increases, so too could the number of cars you could own, provided you want to own more cars.
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