Sampling Design and Sampling Distribution


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An overview of sampling design and type of samples.

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  • Before taking a sample, researchers must make several decisions
  • Before taking a sample, researchers must make several decisions
  • Before taking a sample, researchers must make several decisions

    A list of elements from which the sample may be drawn
    is called a sampling frame. The sampling frame is also called the working population because these units will eventually provide units involved in analysis.
  • Sampling Design and Sampling Distribution

    1. 1. Sampling Design and Sampling Distributions Presented By: • Mudit Singla (51) • Vikas Sonwane (53) • Manisha Tripathy(55) • Vaibhav Sood (57) • Aayush Velaga (59)
    2. 2. Target Population The target population is the collection of elements or objects that possess the information sought by the researcher and about which inferences are to be made.
    3. 3. Terminology – An element is the object about which or from which the information is desired, e.g., the respondent – A sampling unit is an element, or a unit containing the element, that is available for selection at some stage of the sampling process – Extent refers to the geographical boundaries – Time is the time period under consideration
    4. 4. Important qualitative factors that determine the sample size – The importance of the decision – The nature of the research – The number of variables – The nature of the analysis – Sample sizes used in similar studies – Incidence rates – Completion rates – Resource constraints
    5. 5. The Sampling Frame Define the target population Select a sampling frame Conduct fieldwork Determine if a probability or non-probability sampling method will be chosen Plan procedure for selecting sampling units Determine sample size Select actual sampling units
    6. 6. Statistical Errors The difference between the value of a sample statistic of interest and the value of the corresponding population parameter a statistical error has occurred.
    7. 7. Types of Errors Random Sampling Error • The difference between the sample result and the result of a census conducted using identical procedures • These errors are due to chance fluctuations Systematic Error • Systematic (non sampling) errors result from non sampling factors, primarily the nature of a study’s design and the correctness of execution • These are not due to chance fluctuations
    8. 8. Illustration
    9. 9. Classification of Sampling Techniques Sampling Techniques Nonprobability Sampling Techniques Probability Sampling Techniques Convenience Sampling Judgmental Sampling Quota Sampling Snowball Sampling Systematic Sampling Stratified Sampling Cluster Sampling Other Sampling Techniques Simple Random Sampling
    10. 10. Types of Non probability sampling Convenience Sampling Judgment Sampling Quota Sampling Snowball sampling
    11. 11. • The sampling procedure of obtaining those people or units that are most conveniently available. • Best used for exploratory research. Convenience Sampling
    12. 12. • A non probability sampling technique in which an experienced individual selects the sample based on personal judgment about some appropriate characteristics of the sample member Judgment Sampling
    13. 13. • A non probability sampling procedure that ensures that various subgroups of a population will be represented on pertinent characteristics to the exact extent that the investigator desires. • POSSIBLE SOURCES OF BIAS – haphazard selection of subjects • ADVANTAGES – Speed of data collection – Lower costs – Convenience Quota Sampling
    14. 14. • A sampling procedure in which initial respondents are selected by probability methods and additional respondents are obtained from information provided by the initial respondents. • It uses referrals for selecting respondents • ADVANTAGES – Reduced sample size – Reduced cost Snowball sampling
    15. 15. Probability Sampling The sampling techniques where selection procedure is based on chance are called probability sampling techniques.
    16. 16. Types of Probability Sampling Simple Random Sampling Systematic Sampling Stratified Sampling Proportional versus Disproportional Sampling Cluster Sampling Multistage area sampling
    17. 17. The sampling procedure that ensures each element in the population will have an equal chance of being included in the sample is called simple random sampling. Simple Random Sampling
    18. 18. A sampling procedure in which a starting point is selected by a random process and then every nth number on the list is selected. Systematic Sampling
    19. 19. A probability sampling procedure in which simple random subsamples that are more or less equal on some characteristic are drawn from within each stratum of population. Stratified Sampling
    20. 20. Proportional A stratified sample in which the number of sampling units drawn from each stratum is in proportion to the population size of that stratum. Disproportional A stratified sample in which the sample size for each stratum is allocated according to analytical considerations Proportional versus Disproportional Sampling
    21. 21. An economically efficient sampling technique in which the primary sampling unit is not the individual element in the population but a cluster of element; clusters are selected randomly. Cluster Sampling
    22. 22. Sampling that involves using a combination of two or more probability sampling techniques Multistage area sampling
    23. 23. Selecting an Appropriate Sample Design A researcher who must decide on the most appropriate sample design for a specific project will identify a number of sampling criteria and evaluate the relative importance of each criterion before selecting a sampling design.
    24. 24. Sampling Criterion • Degree of Accuracy – Depends on the researcher’s tolerance for errors in sampling and requirements of the project • Resources – Depends on the researcher’s financial and human resource constraints • Time – Depends on the deadline of the project completion • Advance Knowledge of the Population – Depends on the availability of details of population characteristics • National vs Local – Depends on the geographic proximity of the population elements
    25. 25. Internet Sampling Advantages • Allow researchers to reach a large sample rapidly • Sample size requirements can be met quickly • Easier to carry out • Less costly Disadvantages • Lack of computer ownership and internet access • Unrepresentative of all target populations
    26. 26. • Volunteer respondents • Unrestricted/convenience samples • Arrive haphazardly • Random selection of sample units is a better option • Done through Pop-up ads • Problem of over representing the frequent visitors to the site • Can be controlled by several techniques like cookies, prescreening etc • Valuable if the target population is defined as visitors to a particular Web site Web Site Visitors
    27. 27. Panel Samples • Drawing a probability sample from an established consumer panel or other pre-recruited membership panel • Yields a high response rate • Easier to select the panelists based on the data of their previously answered questionnaires • Panelists are compensated for their time with a sweepstakes, a small cash incentive, or redeemable points, etc • Allows the company to draw simple random samples, stratified samples, and quota samples
    28. 28. Recruited Ad Hoc Samples • A sampling frame of e-mail addresses on an ad hoc basis • Can be done online or offline • Can be compiled from many sources, including customer/client lists, advertising banners on pop-up windows that recruit survey participants, online sweepstakes, and registration forms • Respondents maybe contacted by “snail mail” or by telephone to ask for their e-mail addresses and obtain permission for an Internet survey • Offline techniques used are random-digit dialing and short telephone screening interviews
    29. 29. Opt-in Lists • To give permission to receive selected e-mail, such as questionnaires, from a company with an internet presence • E-mail is sent only to authorized recipients • Each individual has to confirm and reconfirm their consent to participate in the survey • Unsolicited survey request is treated as spam • High response rate cannot be expected from the individuals who have not agreed to be surveyed • It can lead to complaints to the Internet Service Providers and the survey site may be shut down