## Tuesday, May 10, 2016

### 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

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