Explain the importance of random sampling

Explain the importance of random sampling. What problems/limitations could prevent a truly random sampling and how can they be prevented?

Random sampling is a method of asking a question for information in an indiscriminate way. For example, a questionnaire is given out in an unsystematic way to a group or population so that every person within that group or population has a chance of submitting information for analysis ("Simple Random Samples," n.d.). Random sampling is the easiest way to try to ensure that the population’s voice will be heard and also this is more accurate than picking specific individuals whose ideas may be what the researchers hope will lead to a specific result. Basically, by using random sampling, there is less chance of the resulting analysis being skewed.

Unfortunately, there are problems with random samples. This type of sampling requires people within the population to volunteer to give information ("Simple Random Samples," n.d.). These people are usually the ones that have the strongest opinions on the subject being analyzed. Therefore, the question this brings up is whether this is an accurate representation of the population. While random sampling is one of the best ways to gather information from a group, it is not without its problems.

NEDARC - Random Selection. (n.d.). Retrieved December 16, 2014, from http://www.nedarc.org/statisticalhelp/selectionAndSampling/randomSelection.ht ml Simple Random Samples. (n.d.). Retrieved December 16, 2014, from https://www.ma.utexas.edu/users/mks/statmistakes/SRS.html Explain each sampling technique discussed in the “Visual Learner: Statistics” in your own words, and give examples of when each technique would be appropriate.

There are three different types of sampling listed in “Visual Learner: Statistics”. These categories are convenience, cluster, random, stratified, and systematic sampling.

Convenience sampling is exactly what the words imply. The sampling is done by convenience or whichever people within the population are easiest to get information from. Therefore the results are skewed based on whomever was closer or easier to get a hold of. An example of this would be a restaurant handing out samples at a college and inquiring what the group thought of the food. The results would be skewed due to the fact that it depended on which students happened to walk by and have time to sample the food and answer questions.

Cluster sampling is where a portion or cluster of a group is targeted instead of the whole group.

This is most commonly used in market research such as asking one large neighborhood that

encompasses all economic levels in order to respond for an entire city on what they thought of the amenities in the city (parks, dog parks, schools, etc). This one cluster’s (neighborhood)opinion would be a representation for the entire city.

Random sampling is essentially people in a population are polled indiscrimantely. This is one the fairest ways to sample a group. An example of this would be surveys that are sent to random patients in a hospital. The people surveyed are randomly selected to participate in this questionnaire. The answers that are received are then used to understand how the hospital is doing as a whole and any areas that might need some work.

Stratified sampling is used when the populations that needs to be surveyed varies greatly. In this type of situation, the different areas must be surveyed in order to show an overall result. One example of this would be before a political election. Some politicians survey different areas of a population by making phone calls to registered voters. This way they can get a good idea how there are going to do in an election.

Systematic sampling is where you survey specific people within a population by picking a start point and then systematically questioning a person at pre-specified numbers. For instance, you start with the second person and survey every 4th person until you get to a tenth of the population. This could be used if you are canvasing a neighborhood to survey a subject like the neighborhood’s home owners association.

There are multiple ways to do sampling. It depends on what you are doing it for and why. No matter if you use convenience, cluster, random, stratified, or systematic sampling it is important to understand the difference and use the appropriate one for what you are surveying.