There are six main reasons for sampling instead of doing a census. They are given as under:
1. Economy
2. Timeliness
3. Very large population
4. Nonaccessible population
5. Destructiveness of the population
6. Accuracy.
1. Economy
2. Timeliness
3. Very large population
4. Nonaccessible population
5. Destructiveness of the population
6. Accuracy.
Sampling Error
Sampling error is the difference between sample and population which is due solely to the particular unit that happens to have been selected. There are two main causes of sampling error. One is chance and the other is sampling bias. Chance, which is the error that occurs just because of chance. Sampling bias, it is the tendency to favor the selection of units that have some particular characteristics.
Non-sampling error
Non- sampling error are those that occur due to the manner in which observation are made.
Characteristic of a Random Sampling
Following are the main characteristics of a random sampling: In Random Sampling
1. Every element of a sample has an equal chance of being selected.
2. Although in random sampling every element of the population has a known probability of being selected yet we can’t predict with accuracy that a particular element will be selected next.
3. We must be able to draw a sample that includes every possible combination of units from the sampling frame, no matter how improbable the combination.
