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Sampling Design

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Vasanthagopal R
Vasanthagopal R

This document discusses sampling design for research. It explains that sampling design refers to the method used to collect data from a subset of a population. A proper sampling design starts with a sample that is representative of the population. There are two main types of sampling: census, which investigates all individuals in a population, and sampling, which uses a small number from the larger population due to constraints. The document outlines key concepts in sampling design including the target population, study population, sampling frame, probability and non-probability sampling methods, and factors to consider for an appropriate sample size and design.

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Sampling Design R.VASANTHAGOPAL PhD University of Kerala
26 April 2020 R.Vasanthagopal PhD 2 Research  Research-  organized set of activities  to find practical solution  for a realistic problem  supported by data
Research Process  Formulating the research problem  Survey and review of literature  Asking research questions and developing hypothesis  Deciding on the research design  Sampling design  Collecting data  Analysis and interpretation of data  Testing the hypotheses  Findings, conclusion and suggestions  Report writing 26 April 2020 R.Vasanthagopal PhD 3
Sampling Design….. 26 April 2020 R.Vasanthagopal PhD 4 Design of a sample refers to the method used to collect the data A proper sampling design must start with a sample which is representative of the population
Census Vs. Sampling 26 April 2020 R.Vasanthagopal PhD 5 Investigation of all individual elements Using a small number of items of larger population Impracticable to survey the entire population Budget constraints Time constraints Immediate need of results
Target Population, Study Population and Sample 26 April 2020 R.Vasanthagopal PhD 6 Sampling frame: The list from which the potential respondents are drawn viz. list of employees
Sampling Scheme/Methods/Techniques 26 April 2020 R.Vasanthagopal PhD 7 All units in the population have an equal probability of being chosen Sample selection not based on the rationale of probability theory
Probability Vs. Non-probability Sampling 26 April 2020 R.Vasanthagopal PhD 8
What is Appropriate Sample Design?  Degree of accuracy  Resources  Time  Need for statistical analysis  Representative of the population  Appropriately sized (the larger the better)  Random (selections occur by chance) 26 April 2020 R.Vasanthagopal PhD 9
Determination of Sample Size A survey estimated that 20% of all Indians aged 21 to 35 drove under the influence of alcohol. A similar survey is planned for Kerala. They want a 95% confidence interval to have a margin of error of 0.04. 26 April 2020 R.Vasanthagopal PhD 10 n=.20(1-.20)1.96x1.96/.04x.04 =384.2 Note: z is the z-score, e.g. 1.645 for a 90% confidence interval,1.96 for a 95% confidence interval, 2.58 for a 99% confidence interval Note: Typical surveys have margins of error ranging from less than 1% to something of the order of 4% - we can choose any margin of error we like but need to specify it. Sample size formula n=N/1+Ne2 Solvin’s(1960) Formula(When population is known. Where e=Margin of error

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Sampling Design

  • 2. 26 April 2020 R.Vasanthagopal PhD 2 Research  Research-  organized set of activities  to find practical solution  for a realistic problem  supported by data
  • 3. Research Process  Formulating the research problem  Survey and review of literature  Asking research questions and developing hypothesis  Deciding on the research design  Sampling design  Collecting data  Analysis and interpretation of data  Testing the hypotheses  Findings, conclusion and suggestions  Report writing 26 April 2020 R.Vasanthagopal PhD 3
  • 4. Sampling Design….. 26 April 2020 R.Vasanthagopal PhD 4 Design of a sample refers to the method used to collect the data A proper sampling design must start with a sample which is representative of the population
  • 5. Census Vs. Sampling 26 April 2020 R.Vasanthagopal PhD 5 Investigation of all individual elements Using a small number of items of larger population Impracticable to survey the entire population Budget constraints Time constraints Immediate need of results
  • 6. Target Population, Study Population and Sample 26 April 2020 R.Vasanthagopal PhD 6 Sampling frame: The list from which the potential respondents are drawn viz. list of employees
  • 7. Sampling Scheme/Methods/Techniques 26 April 2020 R.Vasanthagopal PhD 7 All units in the population have an equal probability of being chosen Sample selection not based on the rationale of probability theory
  • 8. Probability Vs. Non-probability Sampling 26 April 2020 R.Vasanthagopal PhD 8
  • 9. What is Appropriate Sample Design?  Degree of accuracy  Resources  Time  Need for statistical analysis  Representative of the population  Appropriately sized (the larger the better)  Random (selections occur by chance) 26 April 2020 R.Vasanthagopal PhD 9
  • 10. Determination of Sample Size A survey estimated that 20% of all Indians aged 21 to 35 drove under the influence of alcohol. A similar survey is planned for Kerala. They want a 95% confidence interval to have a margin of error of 0.04. 26 April 2020 R.Vasanthagopal PhD 10 n=.20(1-.20)1.96x1.96/.04x.04 =384.2 Note: z is the z-score, e.g. 1.645 for a 90% confidence interval,1.96 for a 95% confidence interval, 2.58 for a 99% confidence interval Note: Typical surveys have margins of error ranging from less than 1% to something of the order of 4% - we can choose any margin of error we like but need to specify it. Sample size formula n=N/1+Ne2 Solvin’s(1960) Formula(When population is known. Where e=Margin of error