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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Management Tutorial What is Sampling Q: Explain sampling and its importance in daily life? Ans: Sample is a collection of few units of a large population which is the total target market. Like for a tooth paste market potential research the population is the all households in the country and sample is few households from selected cities and villages. If the market potential is to assess of a metro city than the whole city will be population and the few selected households are the sample
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Explain a sampling method that could be used in this case study: First of all‚ there are a few options for sampling methods in this case study of how the relief workers at disaster sites experience and cope with issues that surface. Considering that at the disaster sites “the medical teams are always over-worked‚ equipment is always misplaced and it is hard to deliverer food and medicine as the infrastructure is often broken down because of earthquakes” (line 7). The subjects of the
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light energy from the sun to make their own food (photosynthesise). Sampling plants 1. RANDOM SAMPLING Random sampling is usually carried out when the area under study is fairly uniform‚ very large‚ and or there is limited time available. When using random sampling techniques‚ large numbers of samples/records are taken from different positions within the habitat. A quadrat frame is most often used for this type of sampling. The frame is placed on the ground (or on whatever is being investigated)
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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 Techniques Worksheet For each description of sampling‚ decide if the sampling technique is A. Simple Random B. Stratified C. Cluster D. Systematic E. Convenience 1. In order to estimate the percentage of defects in a recent manufacturing batch‚ a quality control manager at Intel selected every 8th chip that comes off the assembly line starting with the 3rd‚ until she obtains a sample of 140 chips. 2. In order to determine the average IQ of ninth-grade students‚ a school psychologist
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Random sampling is the purest form of probability sampling. Each member of the population has an equal and known chance of being selected. When there are very large populations‚ it is often difficult or impossible to identify every member of the population‚ so the pool of available subjects becomes biased. Systematic sampling is often used instead of random sampling. It is also called an Nth name selection technique. After the required sample size has been calculated‚ every Nth record is selected
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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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SAMPLING Sampling is the act‚ process‚ or technique of selecting a suitable sample‚ or a representative part of a population for the purpose of determining parameters or characteristics of the whole population. REASONS FOR SAMPLING There are six main reasons for sampling instead of doing a census. These are; * Economy * Timeliness * The large size of many populations * Inaccessibility of some of the population * Destructiveness of the observation * Accuracy or Reliability
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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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