Everything about variable in statistics

What is variable?

Anything that can be measure or counted is called variable. It can be characteristics, number, or quantity, etc but it should measure or count.
For example: income, money, age, house, grade, etc.

There are two main sections of variable:

1: Quantitative variable:
All the things that you can count or measure come in this section.
Like: numerical, height, weight, temperature, etc.
Quantitative variable divided in two sections:
|. Discrete:
All the countable things like Book pages, money, etc come in this section.
|| Continuous:
All measurable things like weight, speed, height, etc, come in this section
2.Qualitative:
All the things that you can't count or measure like location, religion, etc come in this section.

What is Random variable?

All those variables which values are picked by chance are called random variables.
Example: Suppose electric car company makes many number of cars in a year but how many car they will sell in this year, they can't tell or predict that. Here the number of car sells is a random variable because it will happen by chance.

How variables are categorized by counted or measured?

1. Is the data values can be ranked or not?
Ex: 1st, 2nd, etc.

2. Is the data info can be organized into specific categories.
Ex: rural, urban, etc.

3. Is the data can be measured or not?.
Ex: Height, temperature, time, length, etc.

Types of measurement scale.
1. Nominal Scale:
This scale is used for labeling categorize variables or data into groups based on a defined set of attributes, without any quantitative value. Here come categorical values and no ranking or no order values. Here the data are qualitative in nature. So the data cannot be ordered or ranked.
Example: Hair color(black, gray, brown), gender(male, female), etc.

2. Ordinal scale:
In this scale you can rank or order the data depending on the specified criteria. Here you can place the measured data into categories and you can order or rank these categories.

Example:
1. letters grad(A+, B+, C+)
2. excellent, good, poor.
3. 1st, 2nd, 3rd
4. Ratting scale(1-5). Here 1 means poor and 5 means excellent.

3. Interval scale:
It is a quantitative measurement scale. This is an ordered scale where the difference between measurements is a meaningful but this scale doesn't have true zero point.
Example:
Celsius scale to measure temperature. Here there is no difference between 10 and 20 degrees Celsius or 20 and 30 degrees Celsius and we can also see that the scale does not have a true zero point. Because zero degrees Celsius does not mean that there is no temperature.

4.Ratio scale:
It is same interval scale but the difference is ration scale has the true zero point. So we can say that in ratio scale we can measure the difference between two points and also express the differences as ration.