## Need of Sampling and Sampling Methods

Well its time to discuss something about Sampling. But before I think you need to know about "Population". In statistics "Population" is every thing that we wish to study. For example if some manufacturing company wants to find out defects in the boxes (made by their company) for them population is all existing boxes in the warehouse. Boxes may be 100, 1000, 10000 or more depending upon the size of the company.  Due to some reasons (discussed below) it is not possible to check all the boxes, so best way to estimate the defects is get sample form the total number of boxes, examine them and based on finding conclude something about whole population. So before doing any sort of analysis sampling is important task need to be done.

We can not examine whole population because of following reasons:

Well in above example suppose if we have currently 10000 boxes, and each box required approximately 1 minute to examine, that means we need total 10000 minutes to examine all the boxes. Some time it may be possible that once we examine some boxes they can not be used again. For example a ice cream company is interested to find out sugar level in each box. Well practically it is not possible to check sugar level in each box, because once we open it we can not use it again. That means we can not ignore the cost factor in such case. So in case of ice cream if we check each box, that means we have nothing to sell.

There are many other such reasons because of that it is impossible to examine the entire population. So, better way is to choose some sample from the population.

How to select Sample:

Now next question is how to select sample?

Well there are numbers of sampling methods available that can be helpful in different situations. These are:

Random Sampling

Systematic Sampling

Stratified Sampling

Convenience Sampling

Judgment Sampling

Quota Sampling

Snowball Sampling

Cluster (Area) Random Sampling

Multi Stage Sampling