Sampling Methods

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Sampling Methods A great deal of sociological research makes use of sampling. This is a technique aiming to reduce the number of respondents in a piece of research, whilst retaining - as accurately as possible - the characteristics of the whole group. The purpose of taking a sample is to investigate features of the population in greater detail than could be done if the total population was used, and to draw inferences about this population. In addition, at the practical level, a sample is likely to be both cheaper and quicker to investigate. All sampling will involve error and sociologists have developed sampling techniques in order to minimize this error. All methods of sampling make use of a sampling frame. Sampling frame -------------- A sampling frame is the list of members of the total population of interest. From this list a sample to study can be drawn. For example, such a list may be an electoral register, if information about those with voting rights is sought, or the family practitioner committee lists if a health survey is projected, or vehicle registration lists, if car ownership or road transport is under study. Types of sampling ----------------- The random sample For inferences about a population to be valid, the sample must be truly representative, the only way to ensure this is to take a Random sample. This involves using either random numbers or systematic sampling. Random numbers are used to ensure that every individual in a sampling frame has an equal chance of being selected as a member of the sample. Systematic samplinginvolves randomly selecting the first individual fro... ... middle of paper ... ...espondents reply out of a sample of 200, is this 45% or 90% in favour of a particular action if 90 out of the 100 answer yes? Second, there will be choice involved at three levels in the sample and all ca introduce bias. The choosing of the sample, the choosing of questions, and the choosing of significant responses. Finally, there is the judgment of interviewers, especially in quota sampling. Generally, sampling seeks to avoid the possibility of 'freaks' occurring and the larger the sample, the less likelihood there is of this happening. The greater the variety of characteristics in the population being measured, the larger and more carefully designed the sample needs to be. Ultimately, the operation of a sample survey comes down to a running battle against sources of bias - a battle, which is never won.
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