**Common Terms of Statistics**

1. Population:

Totality of individuals or objects about which information is required is known as population.

e.g. population of patients of hepatitis , students of MBA classes at RYK campus etc…

2. Sample:

A small part of the population which is selected to investigate the properties of the population is known as sample.

3. Variable:

A characteristics which changes from individual to individual or object to object is known as variable.

e.g. height of students, income of people, weight of potatoes etc…

Variables are sub-divided into two categories:

3.1 Quantitative Variable:

Any variable which can be measured numerically is known as Quantitative variable.

e.g. income, speed, distance, temperature etc…

Quantitative variable are further divided into two types:

3.1.1 Discrete Variable:

A variable which can assume a finite number of values is known as discrete variable.

e.g. no. of leaves, no. of children etc…

3.1.2 Continuous Variable:

A variable which can have any value in a given interval [a,b] is known as continuous variable. Therefore the number of possible values of a continuous variable is infinite.

e.g. height, weight, distance etc…

3.2 Qualitative Variable:

Any variable which can’t be measured numerically is known as Qualitative variable. It is also known as “Attribute”.

e.g. smoking habit, religion, eye color, etc…

4. Constant:

A characteristic which does not change its value from individual to individual and object to object is called a constant.

OR “A variable which have only one value is called constant.”

5. Measurement Error:

The difference between the actual value (True) and the response we get (Recorded) is measurement error. It may be positive or negative.

5.1. Random Error:

If error is due to human mistake or the direction of error is not the same that it’s said to be a Random Error.

e.g. reading error, human mistake in measurement etc…

5.2 Systematic Error:

If the direction of the error in all data is same then it is called a systematic error.

e.g. Machine error, scale error etc…