Sampling

Sampling

Sampling is the process of selecting units (e.g., people, organizations) from a population of interest so that by studying the sample we may fairly generalize our results back to the population from which they were chosen

Statistical Terms in Sampling

. When we sample, the units that we sample -- usually people -- supply us with one or more responses. In this sense, a response is a specific measurement value that a sampling unit supplies. In the figure, the person is responding to a survey instrument and gives a response of '4'. When we look across the responses that we get for our entire sample, we use a statistic. There are a wide variety of statistics we can use -- mean, median, mode, and so on. In this example, we see that the mean or average for the sample is 3.75. But the reason we sample is so that we might get an estimate for the population we sampled from. If we could, we would much prefer to measure the entire population. If you measure the entire population and calculate a value like a mean or average, we don't refer to this as a statistic, we call it a parameter of the population.

Probability Sampling

A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection.

Some Definitions

* N = the number of cases in the sampling frame

* n = the number of cases in the sample

* NCn = the number of combinations (subsets) of n from N

* f = n/N = the sampling fraction

Simple Random Sampling

The simplest form of random sampling is called simple random sampling

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