DQ 1, Week 2 of HLT-362V
Explain the importance of random sampling. What problems/limitations could prevent a truly random sampling and how can they be prevented?
The importance of random sampling is the use of statistically derived random sampling processes. These ensure that survey results can be fortified as statistically illustrative of the population. Surveys that do not follow these procedures can yield results that lead to misguided market research, strategic, or policy decisions. Any survey in which no attempt is made to randomly select respondents, such as in polls, is likely to produce results that in no way reveal general public opinion. Even if many thousands of individuals participate. It is true that sampling randomly will eliminate systematic bias. The mathematical theorems which validate most frequent statistical procedures relate only to random samples.
The problems/limitations that could prevent a truly random sampling are important because it assures that the conclusions you draw can be applied to your entire population. The subsequent issues that could cause problems with random sampling are if the experimenter selects a sample that is too small and the experimenter does not understand the population.
This can be prevented by using the standard deviation which, is divided by the square-root of the sample number (n), which means that the standard error will be smaller than the population standard deviation, and that it will get progressively smaller as sample size increases. This is logical because a larger sample should yield a better representation of the population mean, and should have less error (Moore & McCabe, 2006).
Reference:
Moore and McCabe (2006), Introduction to the Practice of Statistics, Sample Distribution and Sampling Error, 3rd ed., p