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Calculation of a Sample Size"If you don't believe in random sampling, next time you
go to the doctor for a blood test, have him take it all. IntroductionSampling is at the heart of marketing research. But it
comes at a price. You can never be 100% sure that your sample
statistics show the exact values of the population
parameters. Actually, you can be quite sure that your
results will be a little off from the true population value
you want to estimate. The important question is: How far off
is your sample result? Reliability deals with how confident we
are that the conclusions based on our sample are correct. Accuracy deals with the distance between
the minimum and the maximum value that I report in my
estimate. In general there is a trade-off between accuracy and reliability. If you want to improve both or one of them while the other remains the same, you have to pay a price. That is, you have to increase your sample size. Calculation of the sample sizeIn our research design one of the key questions is how
many respondents we need in order for our results to be both
reliable and accurate. This spreadsheet has four sheets. Two of them calculate confidence intervals for given values of the sample proportion, sample size and level of confidence. One deals with the large population situation, the other with the small population situation. The other two sheets calculate the number of respondents you need such that for the proportions found by your research a certain level of confidence and a certain maximum margin of error are guaranteed. Again we make a distinction between the large population and small population situation. Further considerations
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Last modified
30-10-2012
© Jos Seegers, 2009; English version by Gé Groenewegen. |