Sampling methodologies Sampling It may be defined as a process of selecting units that may be people‚ organizations etc‚ from a larger whole i.e. from a population of interest‚ so that by studying the sample we may come up with general characteristics of the entire population under consideration. Types of sampling methods: Probability sampling Probability sampling is a type of sampling that includes random selection. And in order to achieve random selection‚ it must be
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populations Because it is impossible to count all the members of a large community‚ some form of sampling has to be used. The size of the sample depends on the area to be investigated‚ but can be shown on a graph as shown (right): Beyond this point‚ more samples (= more work) does not increase the reliability of the results. Ideal sample size AQA are very keen that you should know the importance of random sampling. This is essential to avoid bias. In fieldwork‚ this is done by: 1. Lay out two tapes at
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Time | Event | Comments | 9:40 | Having snack on the snack mat‚ gives me his orange “you open this...please” I unpeel his orange and give it back to him. “thank you” | Polite and good Manners‚ but misses words out. | 9:41 | “Egg egg egg” “I had scrambled egg I did” – Joining in with a conversation from child B. “eyeballs‚ Eyeballs” laughing. Pointing at a water bottle in the tray with stickers on. | Still on the snack mat‚ eating. Communicating with child B. Being a bit silly with his snack
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Sampling distribution The sampling distribution is the distribution of the values of a sample statistic computed for each possible sample that could be drawn from the target population under a specified sampling plan. Because many different samples could be drawn from a population of elements‚ the sample statistics derived from any one sample will likely not equal the population parameters. As a result‚ the sampling distribution supplies an approximation of the true value’s population parameters
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CHAPTER 12 SAMPLING MECHANICS Sampling is an activity that involves the selection of individual people‚ data or things‚ from a target population/universe. A population‚ or universe‚ is the entire set people data or things that is the subject of exploration. A census involves obtaining information‚ not from a sample‚ but rather from the entire population or universe. A sample (as opposed sampling) is a subset of the population/universe. For Marketing Research purposes‚ sampling usually
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Population and Sampling MTH/231 Fahad M. Gohar Statistical data dates back to as early as Ancient Greek time‚ where it was introduced by John Graunt‚ William Petty and Pascal in the 16th century. It was then re-introduced by Gottfriend Achenwall in the 17th century. This was a very exciting time for scientists‚ astronomers and physicists alike as it raised the confidence and knowing that the laws of nature were not of divine intervention. As the years went on‚ new mathematical
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Concept and basics of probability sampling methods One of the most important issues in researches is selecting an appropriate sample. Among sampling methods‚ probability sample are of much importance since most statistical tests fit on to this type of sampling method. Representativeness and generalize-ability will be achieved well with probable samples from a population‚ although the matter of low feasibility of a probable sampling method or high cost‚ don’t allow us to use it and shift us to the
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from a population is known as sample design. It describes various sampling techniques and sample size. It refers to the technique or procedure the researcher would adopt in selecting items for the sample. STEPS IN SAMPLE DESIGN Type of universe Sampling unit Source List Size of Sample Parameters of Interest Budgetary Constraint Sampling Procedure CRITERIA OF SELECTING A SAMPLING PROCEDURE Inappropriate sampling frame Defective measuring device Non-Respondents Indeterminancy
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Session 5 Topic: Sampling Theory/ Techniques and Discussions Project Brief ◦ Expectations and deliverables (Deadline October 1‚ 2010- EOD) Sampling basics ◦ Fundamental Issues ◦ Errors Sampling techniques ◦ Probabilistic ◦ Non-probabilistic Discussions © Krishanu Rakshit‚ IIM Calcutta 28 September‚ 2010 2 When do we use a ‘sample’ When do we use a census (population) Sampling errors ◦ Difference between a measure from sample and the measure
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Sampling Procedures There are many sampling procedures that have been developed to make sure that a sample really represents the target population. Simple Random Sampling In simple random sampling‚ every individual in the target population has an equal chance of being part of the sample. This requires two steps: 1. Obtain a complete list of the population. 2. Randomly select individuals from that list for the sample. In a study where the unit of analysis is the student‚ the researcher
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