Sample

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Sample: Sample is the subset of the population. Why sample? There are several compelling reasons for sampling, including: Lower cost Greater accuracy of results Greater speed of data collection Availability of population elements

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Types of Sampling Designs:

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Probability Sampling The unrestricted, simple random sample is the simplest form of probability sampling since all probability samples must provide a known nonzero chance of selection for each population element, the simple random sample is considered a special case in which each population element has a known and equal chance of selection

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Steps in Sampling Design a. What is the relevant population? b. What are the parameters of interest? c. What is the sampling frame? d. What is the type of sample? What size sample is needed? f. How much will it cost? .

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Comparison of probability Sampling Designs

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Comparison of probability Sampling Designs

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Comparison of probability Sampling Designs

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Comparison of probability Sampling Designs

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Comparison of probability Sampling Designs

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Non Probability Sampling With a subjective approach like non probability sampling, the probability of selecting population elements is unknown. There are a variety of ways to choose persons or cases to include in the sample.

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Convenience Sampling Non probability samples that are unrestricted are called convenience samples. They are the least reliable design but normally the cheapest and easiest to conduct. Researchers or field workers have the freedom to choose whomever they find, thus the name convenience. Examples include informal pools of friends and neighbor, people responding to a newspaper’s invitation for readers to state their positions on some public issue or a TV reporter’s “man on the street” intercept interviews, or using employees to evaluate the taste of a new snack food.

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Purposive Sampling A non probability sample that conforms to certain criteria is called purposive sampling. There are two major types Judgment sampling and quota sampling. Judgment Sampling Judgment sampling occurs when a researcher selects sample members to conform to some criterion. In a study of labor problems, you may want to talk only with those who have experienced on the job discrimination.

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Quota Sampling Quota sampling is the second type of purposive sampling. We use it to improve representativeness. The logic behind quota sampling is that certain relevant characteristics the dimensions of the population. If a sample has the same distribution on these characteristic, then it is likely representative of the population regarding other variables on which we have no control. We consider the following Gender: male, female Class level: graduate, undergraduate College: Arts and science, Agriculture, Architecture, Business, Engineering, other Religion: Muslim, Protestant, Catholic, other.

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Snowball sampling Snowball sampling is the process of selecting a sample using networks. To start with, a few individuals in a group or organization are selected and the required information is collected from them. This sampling technique is useful if you know little about the group of organization you wish t study, as you need only to make contact with a few individuals, who can then direct you to the other members of the group. This method of selecting a sample is useful for studying communication patterns, decision making or diffusion of knowledge within a group.