Unit: III

UNIT-III SAMPLING DESIGN

MEANING OF SAMPLE:

A sample refers to a smaller, manageable version of a larger group. It is a subset containing the characteristics of a larger population. Samples are used in statistical testing when population sizes are too large for the test to include all possible members or observations. A sample should represent the population as a whole and not reflect any bias toward a specific attribute. 

Significance of Sample:

Save Time: Contacting everyone in a population takes time. And, invariably, some people will not respond to the first effort at contacting them, meaning researchers have to invest more time for follow-up. Random sampling is much faster than surveying everyone in a population, and obtaining a non-random sample is almost always faster than random sampling. Thus, sampling saves researchers lots of time.

Save Money: The number of people a researcher contacts is directly related to the cost of a study. Sampling saves money by allowing researchers to gather the same answers from a sample that they would receive from the population. Non-random sampling is significantly cheaper than random sampling, because it lowers the cost associated with finding people and collecting data from them. Because all research is conducted on a budget, saving money is important. Collect Richer Data: Sometimes, the goal of research is to collect a little bit of data from a lot of people (e.g., an opinion poll). At other times, the goal is to collect a lot of information from just a few people (e.g., a user study or ethnographic interview). Either way, sampling allows researchers to ask participants more questions and to gather richer data than does contacting everyone in a population.

Essentials of a good sample:

A sample must possess the following essential characteristics.

Adequacy: The size of the sample should be adequate i.e., neither too large nor small but commensurate with the size of the population.

Homogeneity: There should be homogeneity in the nature of all the units selected for the sample. If the units of the sample are of heterogeneous character it will impossible to make a comparative study with them.

 Independent ability: The method of selection of the sample should be such that the items of the sample are selected in an independent manner. This means that lection of one item should not influence the selection of another item in any manner that each item should be selected on the basis of its own merit.

Goal-oriented: A sample design should be goal oriented. It is means and should be oriented to the research objectives and fitted to the survey conditions.

Accurate representative of the universe: A sample should be an accurate representative of the universe from which it is taken. There are different methods for selecting a sample. It will be truly representative only when it represents all types of units or groups in the total population in fair proportions. In brief sample should be selected carefully as improper sampling is a source of error in the survey.

Proportional: A sample should be proportional. It should be large enough to represent the universe properly. The sample size should be sufficiently large to provide statistical stability or reliability. The sample size should give accuracy required for the purpose of particular study. Random selection: A sample should be selected at random. This means that any item in the