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Sampling techniques

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For this task, you will prepare an annotated outline comparing the different types of sampling techniques. Headings for the outline should be divided between probability and nonprobability sampling. Each sampling technique 
should be described, including when it is best to use the particular method, identify the question type for the particular technique, identify the best method to apply to each technique, and list the type of quantitative design that best fits with the sampling technique.

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Sampling methods are examined.

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Sampling techniques

A sample is the group of people who are selected to be in the study. There are two types of sampling: probability and nonprobability samplings.
Probability Sampling
A probability sampling method is any method of sampling that utilizes some form of random selection (i.e., the likelihood of any one member of the population is known). 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.
• Advantages
 Gives one the ability to describe or predict and then generalize to larger populations
• Disadvantages
 More time and cost than non-probability sampling

Simple Random Sampling - Each member of the population has an equal and independent chance of being selected to be part of the sample. The goal is to select n units out of N such that each combination has an equal chance of being selected.
 Use a table of random numbers, a computer random number generator, or a mechanical device to select the sample.

• Advantages
 Simple to accomplish
 Easy to explain to others
 Because it is a fair way to select a sample, it is reasonable to generalize the results from the sample back to the population.

• Disadvantages
 Not the most statistically efficient method of sampling
 May not get good representation of subgroups in a population

Stratified Random Sample - The profile of the sample matches the profile of the population on some specific characteristic. The goal is to divide your population into homogeneous subgroups (i.e., stratums) and then take a simple random sample in each subgroup in order to more closely represent the population.
 Divide the population into non-overlapping groups (i.e., strata) N1, N2, N3, ... Ni, such that N1 + N2 + N3 + ... + Ni = N (everyone is accounted for and everyone is in one and only one group, N1 may be white males, N2 might be black males, N3 may be white females, etc.). Then do a simple random sample of f = n/N in each strata.
 There are several major reasons why you might prefer stratified sampling over simple random sampling.

Systematic Sampling - Choose a number at random ...

Solution provided by:
Chris Busu, PhD (IP)
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  • BSc, University of Bucharest
  • MSc, Ovidius
  • MSc, Stony Brook
  • PhD (IP), Stony Brook
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