Sampling Techniques and Imortance

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With a single grain of rice, an Asian housewife tests if all the rice in the pot has boiled; from a cup of tea, a tea-taster determines the quality of the brand of tea; and a sample of moon rocks provides scientists with information on the origin of the moon. This process of testing some data based on a small sample is called sampling. Definition : ________________________________________ Sampling is the process by which inference is made to the whole by examining a part. ________________________________________ Purpose of Sampling The purpose of sampling is to provide various types of statistical information of a qualitative or quantitative nature about the whole by examining a few selected units. The sampling method is the scientific procedure of selecting those sampling units which would provide the required estimates with associated margins of uncertainity, arising from examining only a part and not the whole. ________________________________________ Methods of Sample Selection Simple Random Sampling In this method each item of the data ( population) has the same probability of being selected in the sample. The selection is usually made with the help of random numbers. • Suppose there are N=850 students in a school from which a sample of n=10 students is to be taken. The students are numbered from 1 to 850. Since our data runs into three digits we use random numbers that contain three digits. All numbers exceeding 850 are ignored because they do not correspond to any serial numbres in the data. In case the same number occurs again, the repetition is skipped. Systematic Sampling In this method first we have to number the data items from 1 to N. Suppose the sample size be n, then we have to calculate the sampling interval by dividing N by n. And generate a number between 1 and N/n and select that data item to be in the sample. Other items in the

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