Sampling is important part of research investigation. Almost all research studies involve sampling. if the universe is few and researcher can able to collect the data then census method is used where as if the universe is large or infinite then sampling method is more appropriate. A sample is a collection of items or elements from a population or universe which comprises some observations selected from the population. it we consider the population is the universal set then sample is consider as the subset of population. Sampling is the process by which inference is made to the whole by examining only a part. When some of the elements are selected with the intention of finding out something about the population from which they are taken, that group of element is referred as a sample and the process of selection is called sampling. The sampling process is based on the principle that a sufficiently large drawn at random from population will be representative of that population; that is, the sampling group will possess the same characteristics in the same proportions the population. We use sample due to low cost for data collection, greater accuracy of result than sample, greater speed of data collection. If there is infinite population then sample is most for research. To be a representative sample, the sample firstly have **accuracy**, the degree of which bias is absent from sample, secondly have **Precision**, good sample design is precision of estimate (*Researcher know that no sample fully represent its population but he have to measure how closely the sample represent the population. The sampling error must be minimizing as soon as possible.*)

**CHARACTERISTICS OF A GOOD SAMPLE DESIGN**

From what has been stated above, we can list down the characteristics of a good sample design as under:

- Sample design must result in a truly representative sample.
- Sample design must be such which results in a small sampling error.
- Sample design must be viable in the context of funds available for the research study.
- Sample design must be such so that systematic bias can be controlled in a better way.
- Sample should be such that the results of the sample study can be applied, in general, for the universe with a reasonable level of confidence.

**Objectives of Sampling**

- To obtain maximum information from selected elements.
- To obtain the limits of accuracy of the estimates of the population parameters.
- To test the significance of population parameters on the basis of samples statistics.