Notes on Sampling Methods

Important Terms:

1. An element is an object on which a measurement is taken.
2. A population is a collection of elements about which we wish to make an inference.
3. Sampling units are non-overlapping collections of elements from the population that cover the entire population.
4. A sampling frame is a list of sampling units.
5. A sample is a collection of sampling units drawn from a sampling frame.
6. Parameter: numerical characteristic of a population
7. Statistic: numerical characteristic of a sample

Reasons for Sampling:

• Sampling can save money.
• Sampling can save time.
• For given resources, sampling can broaden the scope of the data set.
• Because the research process is sometimes destructive, the sample can save product.
• If accessing the population is impossible; sampling is the only option.

Random Sampling vs Non-random Sampling

Random sampling

• Every unit of the population has the same probability of being included in the sample.
• A chance mechanism is used in the selection process.
• Eliminates bias in the selection process
• Also known as probability sampling

Nonrandom Sampling

• Every unit of the population does not have the same probability of being included in the sample.
• Open the selection bias
• Not appropriate data collection methods for most statistical methods
• Also known as nonprobability sampling

Random Sampling Techniques

Simple Random Sample

• Uses a random number table or a random number generator to select n distinct numbers between 1 and N, inclusively.
• Easier to perform for small populations

Stratified Random Sample

• Population is divided into non-overlapping subpopulations called strata
• A random sample is selected from each stratum
• Proportionate -- the percentage of thee sample taken from each stratum is proportionate to the percentage that each stratum is within the population
• Disproportionate -- proportions of the strata within the sample are different than the proportions of the strata within the population

Systematic Random Sample

• Systematic sampling is often used instead of random sampling.  It is also called an Nth name selection technique. 
• After the required sample size has been calculated, every Nth record is selected from a list of population members. 

Cluster (or Area) Sampling

• Population is divided into nonoverlapping clusters or areas
• Each cluster is a miniature, or microcosm, of the population.
• A subset of the clusters is selected randomly for the sample.

Nonrandom Sampling Techniques

Convenience Sampling:  sample elements are selected for the convenience of the researcher

Judgment Sampling:  sample elements are selected by the judgment of the researcher

Quota Sampling:  sample elements are selected until the quota controls are satisfied

Snowball Sampling:  survey subjects are selected based on referral from other survey respondents

source:
http://www.uky.edu/~kdbrad2/EPE773/Notes/PowerPoint/Chapter5.ppt.
http://www.aueb.gr/users/koundouri/resees/uploads/Chapter07.ppt.