Question

Simple random sampling is usually easy to design and analyze.However,it is not the best design to use in some situations. Explain why

Answer 1

Randomness and Representative Samples

Simple random sampling means that every member of the population has an equal chance of being included in the study. In the candy bar example, that means that if the scope of your study population is the entire United States, a teenager in Maine would have the same chance of being included as a grandmother in Arizona. This is a big advantage, because a truly random sample will be more representative of the population. If you select randomly, there's less chance of sampling bias. It's very unlikely you would end up talking to only white men, for example, which could lead to improper conclusions about the best slogan.

Easy in Small, Defined Populations

If you are a marketing executive interested in selling your candy bar only at one specific high school, simple random sampling has another big advantage: It will be very easy. Random sampling is very convenient when working with small populations that have already been identified and listed. In a high school, for example, the population would be the principal's list of enrolled students. To take a random sample, all you would have to do is number the listed students and use a random number generator to select a few of them for the study. Of course, your results would only tell you how well the slogan worked at that high school, not across the country.

When our entire population is heterogeneus or population have homegeneous subgroups then we can't use simple random sampling. Because in this situation if we used simple random sampling then there is chance that only sub goup of population can be comes in sample and our sample did not represent entire population.