Statistics Sampling

• Sample - it is a unit that is selected from population
• sample - represents the whole population
• sampling - is the process of selecting observations to provide an adequate description and inferences of the population
• Sampling frame - listing of population from which a sample is chosen
• probability sampling - a sampling technique that involves selecting a sample from a population by using a sampling frame
• non-probability sampling - sampling method that does not involve the use of probability sampling
• simple random sampling - all subsets of the frame are given an equal probability: random number generators
• simple random sampling - all subsets are given equal chance
• advantages of simple random sampling:

  • Minimal knowledge of population needed
  • easy to analyze data
• Disadvantages of simple random sampling:

  • Low Frequency of use
  • does not use researcher's expertise
  • larger risk of random error
• stratified random sampling - population is divided into two or more groups called strata
• stratified random sampling - subsamples are randomly selected from each strata
• strata - if the population is divided into two or more groups
• advantages of stratified random sampling:

  • assures the representation of all groups in the sample population
  • characteristics of each stratum can be estimated and comparisons made
• disadvantages of stratified random sampling:

  • requires accurate information on proportions of each stratum
  • stratified lists costly to prepare
• cluster sampling - a sampling technique that involves selecting a number of clusters and then randomly selecting members from each cluster
• cluster sampling - the population is divided into subgroups like family
• cluster sampling - a simple random sampling is taken from each cluster
• advantages of cluster sampling:

  • can estimate characteristics of both cluster and population
• disadvantages of cluster sampling:

  • the cost to reach an element to sample is very high
  • each stage in cluster sampling introduces sampling error-the more stages there are, the more error there tends to be
• systematic random sampling - order all units in the sampling frame, then every Nth number on the list is selected

  N=sampling interval
• advantages of systematic random sampling:

  • moderate cost; moderate usage
  • simple to draw sample
  • easy to verify

  Disadvatage:

  • periodic ordering required
• multistage sampling - carried out in stages, using smaller and smaller sampling units at each stage
• advantage of multistage sampling:

  • more accurate
  • more effective

  Disadvatages:

  • costly
  • each stage in a sampling introduces sampling error-the more stages there are, the more error tends to be
• non-probability units of the samples are chosen on the basis of personal judgement or convenience
• there are no statistical techniques for measuring random sampling error in a non-probability sample
• convenience sampling - involves choosing respondents at the convenience of the researcher
• convenience sampling - a sample is selected from a population that is easy to access
• advantages of convenience sampling:

  • very low cost
  • extensively used/understood

  Disadvatages:

  • variability and bias cannot be measured or controlled
  • Projecting data beyond sample is not justified
  • restriction of generalization
• quota sampling - the population is first segmented into mutually exclusive sub-groups, just as stratified sampling
• advantages of quota sampling:

  • used when research budget is limited
  • very extensively used/understood
  • no need for list of population elements

  Disadvantages:

  • variability and bias cannot be measured/controlled
  • Time consuming
  • projecting data beyond sample is not justified
• Judgmental sampling - researcher employs his/her own "expert" judgement about
• judgmental sampling - the researcher selects participants based on their opinions or beliefs
• advantages of judgmental sampling:

  • there is a assurance of quality response
  • meet the specific objective

  Disadvantages

  • bias selection of sample
  • time consuming process
• snowball sampling - a technique used to gather data from a small group of people to a larger group
• snowball sampling - starts with a key person and introduce the next person to become a chain; chain sampling
• advantage of snowball sampling:

  • Low cost
  • useful in specific circumstances & for locating rare population

  disadvatages:

  • not independent
  • projecting data beyond sample not justified
• self-selection sampling - occurs when you allow each case usually individuals, to identify their desire to take part in the research
• advantages of self-selection sampling:

  • more accurate
  • useful in specific circumstances to serve the purpose

  Disadvantages:

  • More costly due to advertizing
  • mass are left
• sampling errors - errors that occur when a sample is drawn from a population