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 3

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

5. Learning Objective One Define 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 Sampling frame Single member of a population
Listing of all elements
Study sample, if from this frame

10. Learning Objective Two Distinguish Between Target And Accessible Population10

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 Three Discuss Probability And Nonprobability Sampling Procedures15

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. Learning Objective Four Compare Four Methods Of Probability Sampling19

20. Probability Sampling
Simple random
Stratified
Cluster
Systematic

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

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

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

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

25. Disadvantages of Simple Random Sampling
Complete listing of population is necessary.
It is time consuming to use.

26. 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.

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

28. Approaches for Stratified 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

29. Advantages of Stratified Random Sampling (cont’d)
Increases probability of being representative
Ensures adequate number of cases for strata

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

31. 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.

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

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

34. 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

35. Advantages of Systematic Random Sampling
Easy to draw sample
Economical
Time-saving technique

36. Disadvantages of Systematic Random Sampling
Samples may be biased.
After first sample is chosen, no longer equal chance

37. Learning Objective Five Compare Three Methods Of Nonprobability Sampling37

38. 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

39. Nonprobability Sampling
Convenience
Quota
Purposive

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

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

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

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

44. 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.

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

46. Learning Objective Six Determine Which Sampling Technique To Use In Various Types Of Research Studies 46

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

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

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

50. Random Sampling or Random Assignment
Each subject has equal probability of being included.
Random assignment
Procedure to ensure that each subject has equal chance

51. Threefold Randomization Process
Used for experimental studies
Helps represent the ideal study procedure
Steps to ensure the process
Subjects randomly selected from population
Subjects randomly assigned to groups
Experimental treatments randomly assigned to groups

52. Learning Objective Seven Compare Longitudinal And Cross-Sectional Studies52

53. Classification of Research Studies
Longitudinal
Cross-sectional

54. Longitudinal Research Study
Subjects are followed over time.
A cohort study is one example.
Subjects are studied based on
Similar age group
Similar background

55. Longitudinal Research Study (cont’d)
Data are gathered.
Same subjects
Several times
Tells influence of time

56. Cross-Sectional Study
Subjects checked at one point in time
Data collected from groups of people
Data may represent differences in
Ages
Time periods
Developmental states
Important considerations

57. Longitudinal Versus Cross-Sectional Studies
Longitudinal studies
Accurate means of studying changes over time
Studies take a long time to perform.
Cross-sectional studies
Less expensive
Take less time
Easier to conduct

58. Learning Objective Eight Enumerate Factors To Be Considered In Deciding The Size Of The Sample58

59. Sample Size No simple rules
Qualitative studies use much smaller samples than quantitative studies.
Factors to consider for sample sizes in quantitative studies
Homogeneity of population
Degree of precision desired by the researcher
Type of sampling procedure that is used

60. Sample Size (cont’d) Central limit theorem
Sampling distribution of the mean

61. Larger Sample Sizes Many uncontrolled variables are present.
Small differences are expected in members.
Population must be divided into subgroups.
Dropout rate among subjects is expected to be high.
Statistical tests are used that require a minimum sample size.

62. Power Analysis Helps to determine sample size
May prevent type II error
Helps to detect statistical significance

63. Power Analysis (cont’d)
Low power; type II error high
External funding sources require it.
Helps determine the optimum sample size

64. Nursing Research Studies
Usually limited to small convenience samples
Generalizations to total population difficult
Small sample sizes warrant replication studies.
Similar results from replication help with generalization.

65. Learning Objective Nine Discuss Sampling Error And Sampling Bias65

66. Sampling Error Random fluctuations in data
Not under the control of the researcher
Chance variations occur when sample is chosen.

67. Sampling Bias Bias when samples are not carefully selected
All nonprobability sampling methods have it.
May occur in probability sampling methods
Subjects decide not to participate when chosen.
Final sample is now not representative of population.

68. Learning Objective Ten Critique The Sampling Procedure Described In Research Reports And Articles68

69. Critiquing the Population and Samples
Is the target population identified?
Is the accessible population identified?
Was a probability or nonprobability sampling method used?
Is the specific sampling method named?
Is the sampling method described?
Is the sampling method appropriate for the study?

70. Critiquing the Population and Samples (cont’d)
Are the demographic characteristics of the sample presented?
Is the sample size adequate?
Was power analysis used to determine the sample size?
Is the sample representative of the population?

71. Critiquing the Population and Samples (cont’d)
Are potential sampling biases identified?
Is subject dropout discussed?