# Paragraph 5

Please write a Paragraph answering to this discussion below with your opinion. Please include citations and references in alphabetical order in case of another source.

The Visual Learner: Statistics listed five different sampling techniques. Cluster sampling, random sample, simple random sample, stratified sampling, and systematic sampling.

Cluster sampling is dividing a large group into smaller groups (clusters) and then randomly selecting a cluster to survey. Cluster sampling would be good for surveying a large area, because it can drastically reduce the amount of people that must be surveyed. Perhaps for a political survey. However, this could lead to a very skewed response because of simply selecting one area.

Random sampling is when an individual has an equal opportunity of being selected as another individual in the population. An example of random sampling is to place all the options into a hat and pull them from there. This is good for something like assigning Holiday call shifts to the individuals in your department, this way it is random and fair. It is least likely to have skewed results if done properly.

Simple random sampling is similar to random sampling in that each object/item/name has an equal opportunity of being selected. An example for this would be selecting 25 names out of a hat with 250 names in the hat.

Stratified sampling is when a population is divided into at least two groups that share the same characteristics, called strata, and then a person is selected from each group. An example would be to have two classes of college students taking ethics, and then selecting a student from each class.

Systematic sampling is randomly picking a starting point, and then selecting ever x element thereafter. An example would be to pick the third car and then every 7th car after that.

There are five different ways to sample each having advantages and disadvantages. It is important to think about the type of survey and carefully select the best sampling option.

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