營銷調(diào)研sling-資料下載頁
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【導(dǎo)讀】(Zikmund,isnearimpossible,probability. non-probability. sampling.selected.inthedata.evenawareof.SystematicSampling. StratifiedSampling. perfect?random. method.samplewillefrom.sampleisdrawn.Howabout. currentstudy-abroadstudents?numbers.
【正文】 xception: If the population is small enough and the sample is more than 10% of the whole population, the population size can matter. Calculating a Sample Size: Calculation of an appropriate sample size depends upon a number of factors unique to each survey and it is down to the researcher to make decisions regarding these factors. The three most important are: How accurate you wish to be How confident you are in the results What budget you have available The required formula is: s = (z / e)2 Where: s = the sample size z = a number relating to the degree of confidence you wish to have in the result. 95% confidence* is most frequently used and accepted. The value of ?z? should be for 99% confidence, for 95% confidence, for 90% confidence and for 80% confidence. e = the error you are prepared to accept, measured as a proportion of the standard deviation (accuracy) Example Imagine we are estimating mean ine, and wish to know what sample size to aim for in order that we can be 95% confident in the result. Assuming that we are prepared to accept an error of 10% of the population, standard deviation (previous research might have shown the standard deviation of ine to be 8000 and we might be prepared to accept an error of 800 (10%)), we would do the following calculation: Example 2 s = ( / ) s = Sample size would be 385
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