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types of sampling

types of sampling

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  • 1. Sampling methods Group Name: Wailay Group members: Malik Arsalan ALI khan M.Saad M.Shujahat Khawar Abbas 034 058 056
  • 2. Types of probability sampling • Probability sampling • Non probability sampling
  • 3. Probability sampling • A type of sampling in which every element of population has equal chance of selection
  • 4. Types of probability sampling • • • • Simple random sampling Systematic random sampling Stratified random sampling Cluster sampling
  • 5. Simple random sampling • A method of probability sampling in which every unit has known and equal chance of being selected.
  • 6. Method of simple random sampling • With replacement • Without replacement
  • 7. Systematic random sampling • A method of probability sampling in which the defined population is ordered and sample is selected by using skip interval.
  • 8. Method of systematic random sampling • Obtain the ordered list of units • Determine number of units in list and desired sample size • Determine the start point randomly • Select sample by skip interval.
  • 9. Stratified random sampling • A method of sampling in which a population is divided into different subgroups and samples are drawn randomly.
  • 10. Cluster sampling • A method of sampling in which sampling units are selected in groups rather than individually.
  • 11. Non probability sampling • A method of sampling in which every element has unknown and unequal chance of selection.
  • 12. Convenience sampling • convenience sampling is a type of non probability sampling which involves the sample being drawn from that part of the population which is close to hand
  • 13. Judgmental sampling • the researcher chooses the sample based on who they think would be appropriate for the study. This is used primarily when there is a limited number of people that have expertise in the area being researched.
  • 14. Quota sampling • A quota is established (say 65% women) and researchers are free to choose any respondent they wish as long as the quota is met.
  • 15. Snow ball sampling • he first respondent refers a friend. The friend also refers a friend, and so on. Such samples are biased because they give people with more social connections an unknown but higher chance of selection
  • 16. Sample design • A methodological plan to obtain a sample from a given population.
  • 17. Steps • • • • • • Types of population Sampling frame Sampling units Sampling methods Sampling size parameters Budgetary constraints
  • 18. Characteristics of ideal sample design • Must produce representative sample • Must result in less sampling error • Must be feasible in context of available funds. • Should have results which can be applied to whole population. • Should be able to prevent systematic bias.
  • 19. Types of errors in sampling • Sampling error • Non sampling error
  • 20. Sampling error • The difference between a sample statistic and population parameters.
  • 21. How to minimize sampling error sampling error • Increasing sample size • stratification
  • 22. Non sampling error • That does not occur due to sampling.
  • 23. Reasons • • • • • Improper division of sampling units Poor response of responses Bias Intentional bias Unintentional bias