Application of certain queries to less than 100% of the population(group of all items that we are trying to observe and analyze) is known as Sampling. In simple terms, sampling is the process of selection of limited number of elements from large group of elements (population) so that, the characteristics of the samples taken is identical to that of the population. In above examples, suppose you choose 1000 students among 4 millions students. then:
Sampling is a great tool if you have to deal with a huge volume of data and you have limited resources. When you have large population of the data, then it can also be the only option you have.
Merits of Sampling
Sampling have various benefits to us. Some of the advantages are listed below:
- Sampling saves time to a great extent by reducing the volume of data. You do not go through each of the individual items.
- Sampling Avoids monotony in works. You do not have to repeat the query again and again to all the individual data.
- When you have limited time, survey without using sampling becomes impossible. It allows us to get near-accurate results in much lesser time
- When you use proper methods, you are likely to achieve higher level of accuracy by using sampling than without using sampling in some cases due to reduction in monotony, data handling issues etc.
- By using sampling, you can get detailed information on the data even by employing small amount of resources.
Demerits of Sampling
- Every coin has two sides. Sampling also have some demerits. Some of the disadvantages are:
- Since choice of sampling method is a judgmental task, there exist chances of biasness as per the mindset of the person who chooses it.
- Improper selection of sampling techniques may cause the whole process to defunct.
- Selection of proper size of samples is a difficult job.
- Sampling may exclude some data that might not be homogenous to the data that are taken. This affects the level of accuracy in the results.