Sampling techniques & Samples types
- 1. By: Puneet Gupta M.Tech (Future Studies and Planning)
- 2. The process of selecting a number of individuals for a study in such a way that the individuals represent the larger group from which they were selected
- 4. A sample is “a smaller collection of units from a population used to determine truths about that population” The sampling frame A list of all elements or other units containing the elements in a population.
- 5. Population… …the larger group from which individuals are selected to participate in a study
- 6. Why Sample? Get information about large populations Lower cost More accuracy of results High speed of data collection Availability of Population elements. Less field time When it’s impossible to study the whole population
- 7. Define the target population Select a sampling frame Conduct fieldwork Determine if a probability or nonprobability sampling method will be chosen Plan procedure for selecting sampling units Determine sample size Select actual sampling units Stages in the Selection of a Sample
- 8. The sample must be: 1. representative of the population; 2. appropriately sized (the larger the better); 3. unbiased; 4. random (selections occur by chance); What is Good Sample?
- 9. •Probability sample – a method of sampling that uses of random selection so that all units/ cases in the population have an equal probability of being chosen. • Non-probability sample – does not involve random selection and methods are not based on the rationale of probability theory. Types of Sampling Sampling Techniques Probability Non- Probability
- 10. Simple random sample Systematic random sample Stratified random sample Cluster sample Probability (Random) Samples
- 11. Non-Probability Samples – Convenience samples (ease of access) sample is selected from elements of a population that are easily accessible – Purposive sample (Judgmental Sampling) You chose who you think should be in the study – Quota Sampling – Snowball Sampling (friend of friend….etc.)
- 14. SIMPLE RANDOM SAMPLING • Applicable when population is small, homogeneous & readily available • All subsets of the frame are given an equal probability. Each element of the frame thus has an equal probability of selection. A table of random number or lottery system is used to determine which units are to be selected.
- 15. Advantages: Minimal knowledge of population needed Easy to analyze data Disadvantages: Low frequency of use Does not use researchers’ expertise Larger risk of random error
- 16. Simple random sampling Every subset of a specified size n from the population has an equal chance of being selected Sunil Kumar
- 17. • Similar to simple random sample. No table of random numbers – select directly from sampling frame. Ratio between sample size and population size • Then every nth number on the list is selected • N= Sampling Interval Systematic Sampling
- 18. Advantages: Moderate cost; moderate usage Simple to draw sample Easy to verify Disadvantages: Periodic ordering required
- 19. Systematic sampling Every member ( for example: every 20th person) is selected from a list of all population members.
- 20. The population is divided into two or more groups called strata, according to some criterion, such as geographic location, grade level, age, or income. Subsamples are randomly selected from each strata. Sunil Kumar
- 21. Advantages: Assures representation of all groups in sample population Characteristics of each stratum can be estimated and comparisons made Disadvantages: Requires accurate information on proportions of each stratum Stratified lists costly to prepare
- 22. Cluster sampling is an example of 'two-stage sampling' . First stage a sample of areas is chosen; Second stage a sample of respondents within those areas is selected. Population divided into clusters of homogeneous units, usually based on geographical contiguity. Sampling units are groups rather than individuals. A sample of such clusters is then selected. The population is divided into subgroups (clusters) like families. A simple random sample is taken of the subgroups and then all members of the cluster selected are surveyed
- 23. Advantages: Can estimate characteristics of both cluster and population Disadvantages: The cost to reach an element to sample is very high Each stage in cluster sampling introduces sampling error—the more stages there are, the more error there tends to be
- 24. Section 4 Section 5 Section 3 Section 2Section 1
- 26. Convenience sampling involves choosing respondents at the convenience of the researcher. Advantages Very low cost Extensively used/understood Disadvantages Variability and bias cannot be measured or controlled Projecting data beyond sample not justified Restriction of Generalization.
- 28. The population is first segmented into mutually exclusive sub-groups, just as in stratified sampling. Advantages Used when research budget is limited Very extensively used/understood No need for list of population elements Disadvantages Variability and bias cannot be measured/controlled Time Consuming Projecting data beyond sample not justified
- 30. Researcher employs his or her own "expert” judgment about. Advantages There is a assurance of Quality response Meet the specific objective. Disadvantages Bias selection of sample may occur Time consuming process.
- 31. The research starts with a key person and introduce the next one to become a chain Advantages Low cost Useful in specific circumstances & for locating rare populations Disadvantages Not independent Projecting data beyond sample not justified
Editor's Notes
- #18: Click to add notes