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The theory of probability sampling.docx

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David Young

The theory of probability sampling  Probability theory – is a branch of mathematics o This is basis for sampling techniques that produce representative samples  Parameter – summary description of a given variable in a population o i.e mean(summary description) individual income of secretaries at mcmaster (population)  sampling distribution – basis for estimating the parameters of a population o 1. From one case to multiple cases – one case will give an estimate of the population paraments  Other cases chosen randomly would give us the same of slightly different estimates  i.e. one secretary chosen at random will constitute one case, and asking for her income will give us some idea of what the income of secretaries at mcmaster is  but if we ask several more secretaries, we are going to get similar results but their answers will be slightly different as all secretaries do not have the same income (seniority dependant)  sampling distribution can be represented on a graph  y axis – number of secretaries, and x- axis income (in thousands)  graph 1 – will give us a normal curve o 2. From one sample to multiple samples  One sample would give us an estimate of the population parameter if it is chosen randomly  If we get more samples, it will give us the same or slightly different estimates of the population parameters  Every time we draw a sample, if we are choosing the sample randomly the results should be the same – maybe slight different but according to probability theory should be very similar results  I.e. if we drew one sample of 30 secretaries, and another of 30 sec at mac, and then yet another sample of 30 sec at mac and we try to determine the individual income, we should be getting the same answer  Sample 1 – maybe $29 000  Sam
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