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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