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# Populations and Samples

11. Populations and Samples. Learning Objectives. Define Population And Sample Distinguish Between Target And Accessible Population Discuss Probability And Nonprobability Sampling Procedures Compare Four Methods Of Probability Sampling. Learning Objectives.

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## Populations and Samples

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1. 11 Populations and Samples

2. Learning Objectives • Define Population And Sample • Distinguish Between Target And Accessible Population • Discuss Probability And Nonprobability Sampling Procedures • Compare Four Methods Of Probability Sampling

3. Learning Objectives Compare Three Methods Of Nonprobability Sampling Determine Which Sampling Technique To Use In Various Types Of Research Studies Compare Longitudinal And Cross-Sectional Studies Enumerate Factors To Be Considered In Deciding The Size Of The Sample

4. Learning Objectives Discuss Sampling Error And Sampling Bias Critique The Sampling Procedure Described In Research Reports And Articles

5. Learning Objective OneDefine Population And Sample

6. Population • Complete set of persons or objects • Common characteristic • Of interest to the researcher

7. Sample • Subset of a population • Sample represents the population.

8. Sample Selection • Representation of the population • Method for getting the sample • Sample size for the study

9. Sample Terms • Element • Single member of a population • Sampling frame • Listing of all elements • Study sample, if from this frame

10. Learning Objective TwoDistinguish Between Target And Accessible Population

11. Population Terms • Target population • Accessible population

12. Target Population • Definition • Entire group of people or objects • People or objects meet designated set of criteria. • Generalization of the findings

13. Accessible Population • Definition • Group of people or objects • Researcher has access to them.

14. Population Importance • Conclusions based on data • Data from accessible population • Decisions made from study results

15. Learning Objective ThreeDiscuss Probability And Nonprobability Sampling Procedures

16. Types of Sampling Methods • Probability • Nonprobability

17. Probability Sampling • Uses random sampling procedures • Selects sample from elements or members of population • Types • Simple • Stratified • Cluster • Systematic

18. Nonprobability Sampling • Uses nonrandom sampling procedures • Selects sample from elements or members of population • Types • Convenience • Quota • Purposive

19. Probability Sampling • Simple random • Stratified • Cluster • Systematic

20. Random Selection • Key word in sample selection • Every subject has an equal chance.

21. Probability Sampling • Allows researcher to estimate the chance • Helps with inferential statistics with greater confidence • Gives the ability to generalize the findings

22. Simple Random Sampling • Type of probability sampling • Importance of this sampling • Equal chance of selection • Independent chance of selection

23. Advantages ofSimple Random Sampling • Little knowledge of population is needed. • Most unbiased of probability method • Easy to analyze data and compute errors

24. Disadvantages ofSimple Random Sampling • Complete listing of population is necessary. • It is time consuming to use.

25. Steps for Simple Random Sampling • Identify the accessible population or list of elements • Choose the method for getting the sample • Note how easy it is through this example • Names of elements on slips of paper • Papers are placed into a hat. • Individual draws a slip of paper. • Individual continues until sample number is met.

26. Stratified Random Sampling • Type of probability sampling • Population is divided into subgroups or strata. • Simple random sample taken from each strata

27. Approaches forStratified Random Sampling • Proportional stratified sampling • Determine sampling fraction for each stratum • Ensure that this stratum is equal • Proportion in total population • Disproportional stratified sampling • Determine stratum is represented • Used when strata are very unequal • Note the key word disproportional

28. Advantages of StratifiedRandom Sampling (cont’d) • Increases probability of being representative • Ensures adequate number of cases for strata

29. Disadvantages ofStratified Random Sampling • Requires accurate knowledge of population • May be costly to prepare stratified lists • Statistics are more complicated.

30. Cluster Random Stratified Sampling • Large groups or clusters, not people, are selected from population. • Simple, stratified or systematic random sampling may be used during each phase of sampling.

31. Advantages ofCluster Random Sampling • Saves time and money • Arrangements made with small number sampling units • Characteristics of clusters or population can be estimated.

32. Disadvantages ofCluster Random Sampling • Causes a larger sampling error • Requires each member assignment of population to cluster • Uses a more complicated statistic analysis

33. Systematic Random Sampling • Type of probability sampling • Every kth element is selected. • Process • Obtain a listing of population • Determine the sample size • Determine the sampling interval (k = N/n) • Select random starting point • Select every kth element

34. Advantages ofSystematic Random Sampling • Easy to draw sample • Economical • Time-saving technique

35. Disadvantages ofSystematic Random Sampling • Samples may be biased. • After first sample is chosen, no longer equal chance

36. Learning Objective FiveCompare Three Methods Of Nonprobability Sampling

37. Nonprobability Sampling • Sample elements are chosen nonrandomly. • Produces biased sample • Each element of the population may not be included in the sample. • Restricts generalizations made about study findings

38. Nonprobability Sampling • Convenience • Quota • Purposive

39. Convenience Sampling • Chooses the most readily available subject or object • Does not guarantee that the subject or object is typical of the population

40. Snowball Sampling • Type of convenience sampling method • Study subjects recruit other potential subjects. • May be called network sampling • May find people reluctant to volunteer

41. Quota Sampling • Type of nonprobability sampling • Researcher selects sample to reflect characteristics. • Examples of stratum

42. Quota Sampling • Age • Gender • Educational background • Number of elements in each stratum • Number is in proportion to size of total population.

43. Purposive Sampling • Type of nonprobability sampling • Researcher uses personal judgment in subject selection. • Each subject chosen is considered representative of population. • Many qualitative studies use this technique.

44. Nonprobability Sampling Procedures • Advantages • Time • Money • Disadvantages • Nonrandom • Not able to generalize findings

45. Learning Objective SixDetermine Which Sampling Technique To Use In Various Types Of Research Studies

46. Research Studies • Use voluntary subjects • Follow the ethics of research • Subjects must voluntarily agree. • Subjects may refuse to participate.

47. Research Data • Based on voluntary responses from subjects • Biased sample occurs if subjects do not participate.

48. Volunteers As Subjects • Sample selection varies. • Subjects volunteer for a study. • Researcher approaches subjects.

49. Random Sampling orRandom Assignment • Random sampling • Each subject has equal probability of being included. • Random assignment • Procedure to ensure that each subject has equal chance

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