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TYPES OF SAMPLING:
Sampling plans can be grouped under two categories-probability sampling and non-probability sampling. Probability sampling uses a technique by which the researcher ensures the probability, that each element of p~pulation will be included in the sample. That is each element has an equal or known chance of being included. It utilizes some form of random selection because of which greater confidence can be placed in the representativeness of probability samples. Non-probability samples use non-random methods i.e. there is bias in the selection. There is no assurance that every element has a chance of being included or, in other words the researcher cannot estimate the probability that each element will be included in the sample. Refer to Figure 4.1 and note the purpose of probability and non-probability sampling. The population values such as mean of standard deviation is called a Parameter whereas the measured value of the sample is termed statistic. We infer the parameter from the statistic when we know that the sample is a true representative of population. Refer Block 4 for further details of parameter and statistic.
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SIZE OF SAMPLE: Large samples are more representative of the population of interest than the sinall samples. There are no specific rdes for determining the desired sampl
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