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According to Cherry(2016) Simple random sampling is "a subset of individuals that are randomly selected from a population of interest". In addition, it is the basic sampling technique where we select a group of subjects (a sample) for study from a larger group (a population).

Each individual is chosen entirely by chance and each member of the population has an equal chance of being included in the sample. A sample is a smaller subset drawn from that larger population. Because the sample is random, every single member of the group stands an equal chance of being selected to be in the sample.

Why is random sampling important?

Random sampling is important because it helps cancel out the effects of unobserved factors.

Example

If you want to calculate the average height of people in a city and do your sampling in an elementary school, you are not going to get a good estimate. This is because the heights are conditional on a certain value of the unobserved factor "age". So you do not have the unconditional mean.

To make sure that specific levels of the hundreds of unobserved factors, like age, ethnicity, nutrition, gender, air quality, etc. are not conditionalizing your measurement of height, you have to make sure that your sample is collected in a way that on average, different levels of unobserved factors are represented.

As a result, your measurements are not conditional on any specific level of any specific unobserved variable. The best way to do this is to use a random sample.

Problem/Prevention (Horton, 2015)

1. Time- needed to gather the full list of a specific population

2. Capital- necessary to retrieve and contact that list

3. Bias- that could occur when the sample set is not large enough to adequately represent the full population.

I would suggest to raise money from businesses and organizations that the research would affect to help conduct the study. In addition, I would make sure to set a schedule and calendar that is conducive to the members in the research, conducting the research, and organizing the data.

In this way the planning and completion is effective. Lastly, I would make sure that all areas of a population are even and selected so that the set is large enough to represent a full population.

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