(unpublished)‚ © 2008. NOT FOR COMMERCIAL DISTRIBUTION 3 Simple Random Sampling 3.1 INTRODUCTION Everyone mentions simple random sampling‚ but few use this method for population-based surveys. Rapid surveys are no exception‚ since they too use a more complex sampling scheme. So why should we be concerned with simple random sampling? The main reason is to learn the theory of sampling. Simple random sampling is the basic selection process of sampling and is easiest to understand. If everyone in a population
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THEME | AUTHOR 1 | AUTHOR 2 | AUTHOR 3 | AUTHOR 4 | AUTHOR 5 | AUTHOR 6 | Definition of Sampling | Tejero‚E.G.(2006)p.43Sampling affords all the members of the population an equal chance of being selected and becoming a part of the samples of the intended research. | David‚F.P (2005) p.95It is the representative portion of a population or some elements in a population that will represent the entire population. | Gill and Johnson(2002)p.101All surveys are concerned with identifying the ‘research
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The key is the use of statistically derived random sampling procedures. These ensure that survey results can be defended as statistically representative of the population. Surveys that do not follow these procedures can produce results that lead to misguided market research‚ strategic‚ or policy decisions. Any so-called "survey" in which no attempt is made to randomly select respondents‚ such as call-in readers’ or viewers’ "polls"‚ is likely to produce results that in no way reflect overall public
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Sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. Acceptance sampling is used to determine if a production lot of material meets the governing specifications. Two advantages of sampling are that the cost is lower and data collection is faster than measuring the entire population. Sampling is the process of selecting units (e.g.‚ people‚ organizations) from a population of interest so that
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ANSWER: Sampling is that part of statistical practice concerned with the selection of an unbiased or random subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern‚ especially for making predictions based on the statistical inference (Ader‚ Mellenberg & Hand: 2008). There are quite a number of sampling methods that can be employed in research and these include simple random sampling‚ systematic sampling‚ stratified sampling
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Samples and Sampling The term "sampling‚" as used in research‚ refers to the process of selecting the individuals who will participate (e.g.‚ be observed or questioned) in a research study. A sample is any part of a population of individuals on whom information is obtained. It may‚ for a variety of reasons‚ be different from the sample originally selected. Samples and Populations The term "population‚" as used in research‚ refers to all the members of a particular group. It is the group of
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Types of Sampling In applications: Probability Sampling: Simple Random Sampling‚ Stratified Random Sampling‚ Multi-Stage Sampling * What is each and how is it done? * How do we decide which to use? * How do we analyze the results differently depending on the type of sampling? Non-probability Sampling: Why don’t we use non-probability sampling schemes? Two reasons: * We can’t use the mathematics of probability to analyze the results. * In general‚ we can’t count on a non-probability
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There are many ways to select a random sample. Four of them are discussed below: Simple Random Sampling: In this sampling technique‚ each sample of the same size has the same probability of being selected. Such a sample is called a simple random sample. One way to select a simple random sample is by a lottery or drawing. For example‚ if we need to select 5 students from a class of 50‚ we write each of the 50 names on a separate piece of paper. Then‚ we place all 50 names in a hat and mix them thoroughly
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Sampling and Sampling Methods There are many research questions we would like to answer that involve populations that are too large to consider learning about every member of the population. How have wages of European workers changed over the past ten years? Questions such as this are important in understanding the world around us‚ yet it would be impractical‚ if not impossible‚ to measure the wages of all European workers. Generally‚ in answering such questions‚ social scientists examine a fraction
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Purposive sampling Purposive sampling‚ also known as judgmental‚ selective or subjective sampling‚ is a type of non-probability sampling technique. Non-probability sampling focuses on sampling techniques where the units that are investigated are based on the judgement of the researcher. Purposive sampling explained Purposive sampling represents a group of different non-probability sampling techniques. Also known as judgmental‚ selectiveor subjective sampling‚ purposive sampling relies on
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