1. Sampling Design and Procedure
Lecture & Seminar
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2. If you decide whether or not you want to see a new movie or television program on the basis of the “coming attractions” or television commercial previews, are you using a sampling technique? A scientific sampling technique?
Yes, this is a method of sampling. However, this type of sampling is generally not of a scientific nature. The portions shown are generally the most interesting rather than representative portions of those movies. Although a subset of all possible television programs or parts of a movie have been observed, they are not selected with an equal chance of becoming a sample member.

3. Sampling Terminology Population Population (universe)
Sample
Sample
Sample
Population (universe)
Any complete group of entities that share some common set of characteristics.
Population Element
An individual member of a population.
Sample
A subset, or some part, of a larger population.
Census
An investigation of all the individual elements that make up a population.

4. Why Sample? Pragmatic Reasons Accurate and Reliable Results
Destruction of Test Units
Pragmatic Reasons
Budget and time constraints.
Limited access to total population.
Accurate and Reliable Results
Samples can yield reasonably accurate information.
Strong similarities in population elements makes sampling possible.
Sampling may be more accurate than a census.
Destruction of Test Units
Sampling reduces the costs of research in finite populations.

5. Stages in the Selection of a Sample

6. Practical Sampling Concepts
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7. Practical Sampling Concepts
Defining the Target Population
What is the relevant population?
Whom do we want to talk to?
Population is operationally defined by specific and explicit tangible characteristics.
The Sampling Frame
A list of elements from which a sample may be drawn; also called working population.
Sampling Frame Error
Occurs when certain sample elements are not listed or are not accurately represented in a sampling frame.

8. Sampling Units Sampling Unit Primary Sampling Unit (PSU)
A single element or group of elements subject to selection in the sample.
Primary Sampling Unit (PSU)
Secondary Sampling Unit
Tertiary Sampling Unit
Primary Sampling Unit (PSU)
A unit selected in the first stage of sampling.
Secondary Sampling Unit
A unit selected in the second stage of sampling.
Tertiary Sampling Unit
A unit selected in the third stage of sampling.

9. Random Sampling and Non-sampling Errors
Random Sampling Error
The difference between the sample result and the result of a census conducted using identical procedures.
A statistical fluctuation that occurs because of chance variations in the elements selected for a sample.
Non-Sampling (Systematic Sampling) Error
Systematic (nonsampling) error results from nonsampling factors, primarily the nature of a study’s design and the correctness of execution.
It is not due to chance fluctuation.

10. Random Sampling and Nonsampling Errors (cont’d)
Less than Perfectly Representative Samples
Random sampling errors and systematic errors associated with the sampling process may combine to yield a sample that is less than perfectly representative of the population.

11. Errors Associated with Sampling

12. Sampling Technique

13. Probability versus Nonprobability Sampling
A sampling technique in which every member of the population has a known, nonzero probability of selection.
Nonprobability Sampling
A sampling technique in which units of the sample are selected on the basis of personal judgment or convenience.
The probability of any particular member of the population being chosen is unknown.

14. Nonprobability Sampling

15. Nonprobability Sampling: Convenience Sampling
Obtaining those people or units that are most conveniently available

16. Nonprobability Sampling: Judgment (Purposive) Sampling
An experienced individual selects the sample based on personal judgment about some appropriate characteristic of the sample member.

17. RESPONDENT QUOTA (SAMPLE SIZE= 200)
Nonprobability Sampling: Quota Sampling
Ensures that various subgroups of a population will be represented on pertinent characteristics to the exact extent that the investigator desires.
BUYERS
RESPONDENT QUOTA (SAMPLE SIZE= 200)
MEN
40% 80
WOMEN
60%
120

18. Nonprobability Sampling: Snowball Sampling
A sampling procedure in which initial respondents are selected by probability methods and additional respondents are obtained from information provided by the initial respondents.
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19. Probability Sampling Simple Random Sampling Systematic Sampling
Assures each element in the population of an equal chance of being included in the sample.
Systematic Sampling
A starting point is selected by a random process and then every nth number on the list is selected.
Stratified Sampling
Simple random subsamples that are more or less equal on some characteristic are drawn from within each stratum of the population.

20. Probability Sampling: Simple Random Sampling
Assures each element in the population of an equal chance of being included in the sample

21. Probability Sampling : Systematic Sampling
A starting point is selected by a random process and then every nth number on the list is selected

22. Probability Sampling: Stratified Sampling
Simple random subsamples that are more or less equal on some characteristic are drawn from within each stratum of the population

23. Proportional versus Disproportional Sampling
Proportional Stratified Sample
The number of sampling units drawn from each stratum is in proportion to the population size of that stratum.
Disproportional Stratified Sample
The sample size for each stratum is allocated according to analytical considerations.

24. Disproportional Sampling: Hypothetical

25. Probability Sampling: Cluster Sampling
An economically efficient sampling technique in which the primary sampling unit is not the individual element in the population but a large cluster of elements. Clusters are selected randomly.

26. Multistage Area Sampling
Involves using a combination of two or more probability sampling techniques.
Typically, geographic areas are randomly selected in progressively smaller (lower-population) units.
Researchers may take as many steps as necessary to achieve a representative sample.
Progressively smaller geographic areas are chosen until a single housing unit is selected for interviewing.

27. Sampling Technique

28. What is the Appropriate Sample Design?
Degree of accuracy
Resources
Time
Advanced knowledge of the population
National versus local project

29. Internet Sampling is Unique
Website Visitors
Internet surveys use unrestricted samples.
May not be representative.
Panel Samples
Recruited Ad Hoc Samples

30. Determination of Sample Size

31. Frequency Distribution of Deposits

32. Percentage Distribution of Deposits

33. Probability Distribution of Deposits

34. Factors of Concern in Choosing Sample Size
Variance (or Heterogeneity)
A heterogeneous population has more variance (a larger standard deviation) which will require a larger sample.
A homogeneous population has less variance (a smaller standard deviation) which permits a smaller sample.
Magnitude of Error (Confidence Interval)
How precise must the estimate be?
Confidence Level
How much error will be tolerated?

35. Estimating Sample Size for Questions Involving Means
Sequential Sampling
Conducting a pilot study to estimate the population parameters so that another, larger sample of the appropriate sample size may be drawn.
Estimating sample size:

36. Sample Size Example
Suppose a survey researcher, studying expenditures on lipstick, wishes to have a 95 percent confident level (Z) and a range of error (E) of less than $2.00. The estimate of the standard deviation is $ What is the calculated sample size?

37. Sample Size Example
Suppose, in the same example as the one before, the range of error (E) is acceptable at $4.00. Sample size is reduced.

38. Calculating Sample Size at the 99 Percent Confidence Level

39. Determining Sample Size for Proportions

40. Determining Sample Size for Proportions (cont’d)

41. Calculating Example Sample Size at the 95 Percent Confidence Level
753 =
001225 .
922 ) 24
)(.
8416 3 (
035
( . 4 6 (. 96 1. n q p 2

42. Low Dispersion versus High Dispersion

43. LOs Explain reasons for taking a sample rather than a complete census
Describe the process of identifying a target population and selecting a sampling frame
Compare random sampling and systematic (nonsampling) errors
Identify the types of nonprobability sampling, including their advantages and disadvantages
Discuss how to choose an appropriate sample design