It is difficult to make a fully representative sample. There are different ways in which a sample can not be representative. These are called sampling errors or bias, and may result in misleading research outcomes. Sampling errors (bias) refers to deviations of your result from the true parameter. Imagine that you checked all grades of all your fellow students and calculated that on average people scored a 7.4. Imagine someone else who had less time than you who took a sample of 100 students out of the total population. Those 100 students, he finds, score on average a 7.6. Now the true parameter is 7.4 and the sampling error (or bias) is 0.2.
What is sampling error or bias?
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Statistics Magazine: Understanding statistical samples
A statistical sample is a limited number of observations selected from a population on a systematic or random basis, which yield generalizations about the population after it is manipulated mathematically.
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