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This document discusses key concepts in sampling design and procedures. It covers reasons for sampling such as pragmatic and cost reasons. It also discusses defining the target population and sampling frame. The document contrasts probability sampling techniques like simple random sampling, systematic sampling, and stratified sampling with non-probability techniques like convenience sampling and snowball sampling. It discusses factors to consider in determining sample size such as variance, desired confidence level and interval. Sample size formulas for estimating means and proportions are also provided.
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- 1. viewords.wordpress.com Sampling Design and Procedu Lecture & Seminar
- 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?
- 4. Why Sample? Pragmatic Reasons Accurate and Reliable Results Destruction of Test Units www.mktginc.com
- 5. Stages in the Selection of a Sample 165
- 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. 168 Sampling Units Sampling Unit A single element or group of elements subject to selection in the sample. 1. Primary Sampling Unit (PSU) 2. Secondary Sampling Unit 3. Tertiary Sampling Unit
- 9. 169 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 studys design and the correctness of execution.
- 10. 1610 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. Random Sampling and Nonsampling Errors (contd)
- 11. Errors Associated with Sampling 1611
- 13. 1613 Probability 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. Probability versus Nonprobability Sampling
- 15. http://lc.gcumedia.com/hlt362v/the-visual-learner/convenience-sampling.html Nonprobability Sampling: Convenience Sampling Obtaining those people or units that are most conveniently available
- 16. www.memrise.com Nonprobability Sampling: Judgment (Purposive) Sampling An experienced individual selects the sample based on personal judgment about some appropriate characteristic of the sample member.
- 17. 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. slides.com
- 19. 1619 Probability Sampling Simple Random 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. www.nedarc.org 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 http://lc.gcumedia.com/hlt362v/the-visual-learner/systematic-sample.html
- 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 http://lc.gcumedia.com/hlt362v/the-visual-learner/stratified-sample.html
- 23. 1623 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. Proportional versus Disproportional Sampling
- 25. 1625 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. http://lc.gcumedia.com/hlt362v/the-visual-learner/cluster-sampling.html
- 26. 1626 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.
- 28. 1628 What is the Appropriate Sample Design? Degree of accuracy Resources Time Advanced knowledge of the population National versus local project
- 29. 1629 Internet Sampling is Unique Website Visitors Internet surveys use unrestricted samples. May not be representative. Panel Samples Recruited Ad Hoc Samples
- 31. Frequency Distribution of Deposits 1731
- 32. Percentage Distribution of Deposits 1732
- 33. Probability Distribution of Deposits 1733
- 34. 1734 Factors of Concern in Choosing Sample Size 1. 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. 2. Magnitude of Error (Confidence Interval) How precise must the estimate be? 3. Confidence Level How much error will be tolerated?
- 35. 1735 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: Estimating Sample Size for Questions Involving Means
- 36. 1736 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 $29.00. What is the calculated sample size?
- 37. 1737 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 17-38
- 39. Determining Sample Size for Proportions 17-39
- 40. Determining Sample Size for Proportions (contd) 17-40
- 41. 753 = 001225 . 922 . = 001225 ) 24 )(. 8416 . 3 ( = ) 035 ( . ) 4 )(. 6 (. ) 96 1. ( n 4 . q 6 . p 2 2 = = = Calculating Example Sample Size at the 95 Percent Confidence Level 17-41
- 42. Low Dispersion versus High Dispersion 1742
- 43. LOs 1. Explain reasons for taking a sample rather than a complete census 2. Describe the process of identifying a target population and selecting a sampling frame 3. Compare random sampling and systematic (nonsampling) errors 4. Identify the types of nonprobability sampling, including their advantages and disadvantages 5. Discuss how to choose an appropriate sample design