Sampling methods

Type :

Presentation

Pages :

9 pages

Format :

.doc

Published date :

01/16/2009

Category :

Arts & media

Sub category :

Journalism

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Summary :

Introduction.
Meaning of Probability sampling.
Simple random sampling.
Systematic sampling.
1. Advantages and disadvantages.
Stratified random sampling.
Random route sampling.
Multistage sampling.
Cluster sampling.
Non-probability sampling.
1. Advantages.
Convenience sampling.
Quota sampling.
Judgemental sampling.
Definition of the common terms used in sampling.
1. A sampling frame.
2. A survey.
3. A sampling error.
4. A respondent.
5. A sample.
6. A random sampling.
7. Bias.
8. Standard error.
Sources.

Abstract

As time and resources available are limited, we cannot interview all members of a population. Therefore, researchers use sampling to obtain the information they need. They select a limited number of people (a sample) to represent the characteristics of a whole population. There are different methods to select a sample. We can divide them into two major groups: the probability sampling and the non-probability sampling. A good sample survey can give important and interesting results. However, a bad sample survey (wrong people interviewed) can have disastrous results on a company, for example. When you use a probability sampling method, you must find some process or procedure that assure that the different units in your population have equal probabilities of being chosen in the sample for the survey being conducted. It is scientific, operationally convenient and simple in theory. You give a number to every member of the population. Then you use a table of random numbers, a computer random number generator or a mechanical technique (to close your eyes and pull out the numbers which refer to people) to select your sample. Finally, you pull out a number and you interview the person who has this number.