Statistics

Statistics

6.2 Basic Terms

• Sampling frame: The source or population from which the sample is taken. • Probability sampling: For this sampling technique, every possibility (characteristics) within the given population has an equal opportunity or likelihood of being selected for the sample. This sampling method produces an unbiased representation of the population. • Non-probability sampling: For this sampling technique, not every possibility (characteristic) within the given population has an equal opportunity or likelihood of being selected for the sample. This sampling method can produce a biased or skewed representation of the population. • Simple random sample: This is the most common of the sampling techniques. During simple random sample selection, all subsets of the given frame have an equal opportunity of being selected. • Systematic sampling: This technique arranges the population based on some pre-determined order. The sample is then selected at a determined interval from the list. Systematic sampling begins with a random sample and then implements a non-random selection from a formed list. This allows the population to be clustered. Imagine trying to sample New York City. Instead of sampling each block of the city, you may group the blocks and sections and decide to sample every 20th block. • Stratified sampling: During this sampling technique, the population experiences and is organized into distinct categories or classifications. The sampling frame is then organized into categories also called strata. The individual stratums are then randomly sampled as independent sub-populations. • Cluster sampling: With a large target population of interest, sometimes sampling is clustered or grouped by geography or other defining population characteristics (such as generations). • Panel sampling: This is very similar to systemic sampling. First, a given population is selected from a random list of participants. The sample is then reduced by asking questions that would narrow down the given sample. You may have a list of all freshmen at a given college; you can then narrow the list down by asking questions that might pertain to your characteristic of interest. Let’s say you want only freshmen who eat yogurt for breakfast. You may ask the original group if they eat breakfast, then the participants that answer no, will be removed from study consideration.

6.3 Common Sampling Techniques

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