**Meaning of sample**

A Finite subset of population, selected from it, with the objective of investigating its properties is called ‘sample’. The number of units in the sample is known as sample size. Sample helps in drawing conclusion about the characteristics of the population. After inspecting the sample we draw the conclusion to accept it or reject it. For example by examining a handful of pulses we decide whether to buy it or not. So buy the whole quantity only on the basis of a sample.

This is the definition or meaning of sampling.

**Principles of sampling**

1) **Principle or** **Law of statistical regularity**:this law is based upon mathematical theory of probability. It is based upon the following two conditions.

i) * Large sample size*: as the sample size increases, the true characteristics of the population are more likely to reveal.

ii) ** Random selection**: the sample should be selected randomly in which each and every unit of the universe has an equal chance of being selected.

2) **Principle of inertia of large numbers**: – it is based upon the concept that as the sample size increases the better results we will get. For example if we have to study the weight of the students studying in a college then fairly adequate sample of the students help us to arrive at good results.

3) **Principle of validity**: – if valid tests are derived only then sampling design is termed as valid.

4) **Principle of optimization**: – this principle states that with the help of sample one must be able to get optimum results with maximum efficiency and minimum cost.

These are the principles of sampling in statistics.