Sample and sampling techniques
- 1. Amobi P. Chiamogu SAMPLE AND SAMPLING TECHNIQUES Amobi P. Chiamogu A paper delivered at a Research Methodology and Project Writing Workshop by the Department of Public Administration, Federal Polytechnic, Oko from 12-13 August, 2016 at the New CBT Hall of the Polytechnic
- 2. STUDY OBJECTIVES Develop an understanding about different sampling methods Distinguish between probability & non probability sampling Discuss the ways of determining Samples Sizes
- 3. A sample is “a smaller (but hopefully representative) collection of units from a population used to determine truths about that population” (Field, 2005) Sampling refers to the selection of some part of an aggregate or totality on the basis of which a judgment or inference about the aggregate is made (Chiamogu and Onwughalu, 2014) Why sample? Resources (time, money) and workload Gives results with known accuracy that can be calculated mathematically The sampling frame is the list from which the potential respondents are drawn
- 4. 3 factors that influence sample representativeness Sampling procedure Sample size Participation (response) SAMPLING Contd When do you sample the entire population? When your population is very small When you have extensive resources When you don’t expect a very hi-response DETERMINATION OF SAMPLE SIZE TARO YAMANE SURVEY MONKEY APPLICATIONS n = 𝑁 1 + 𝑁(𝑒)2 https://www.surveymonkey.com/mp/sample-size- calculator http://www.surveysystem.com/sscalc.htm
- 5. • Probability (Random) Samples • Simple random sample • Systematic random sample • Stratified random sample • Multistage sample • Cluster sample • Non-Probability Samples • Convenience sample • Purposive sample • Quota Sampling Techniques
- 6. Two general approaches to sampling are used in social science research. With probability sampling, all elements (e.g., persons, households) in the population have (relatively) equal chances of being included in the sample, and the mathematical probability that any one of them will be selected can be calculated. With nonprobability sampling, in contrast, population elements are selected on the basis of their availability (e.g., because they volunteered) or because of the researcher's personal judgment that they are representative. The consequence is that an unknown portion of the population is excluded (e.g., those who did not volunteer or those whom his biases did not favour). One of the most common types of nonprobability sample is called a convenience sample – not because such samples are necessarily easy to recruit, but because the researcher uses whatever individuals are available rather than selecting from the entire population. Because some members of the population have no chance of being sampled, the extent to which a non-probability sample – regardless of its size – actually represents the entire population cannot be known
- 7. Sampling Process This comprises several stages: Defining the population of concern Specifying a sampling frame, a set of items or events possible to measure Specifying a sampling method for selecting items or events from the frame Determining the sample size Implementing the sampling plan Sampling and data collecting Reviewing the sampling process
- 8. 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. • It provides for greatest number of possible samples. This is done by assigning a number to each unit in the sampling frame. • A table of random number or lottery system is used to determine which units are to be selected.
- 9. SYSTEMATIC SAMPLING • This relies on arranging the target population according to some ordering scheme and then selecting elements at regular intervals through that ordered list. • Systematic sampling involves a random start and then proceeds with the selection of every nth element from then onwards. In this case, n=(population size/sample size). • It is important that the starting point is not automatically the first in the list, but is instead randomly chosen from within the first to the nth element in the list. • A simple example would be to select every 10th name from the telephone directory (an 'every 10th' sample, also referred to as 'sampling with a skip of 10').
- 11. STRATIFIED SAMPLING… • Finally, since each stratum is treated as an independent population, different sampling approaches can be applied to different strata. • Drawbacks to using stratified sampling. • First, sampling frame of entire population has to be prepared separately for each stratum • Second, when examining multiple criteria, stratifying variables may be related to some, but not to others, further complicating the design, and potentially reducing the utility of the strata. • Finally, in some cases (such as designs with a large number of strata, or those with a specified minimum sample size per group), stratified sampling can potentially require a larger sample than would other methods
- 12. CLUSTER SAMPLING • This 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. • All units from the selected clusters are studied.
- 13. QUOTA SAMPLING
- 14. CONVENIENCE SAMPLING • Often referred to as accidental or haphazard sampling. • It involves the sample being drawn from that part of the population which is close to hand. That is, readily available and convenient. • The researcher using such a sample cannot scientifically make generalizations about the total population from this sample because it would not be representative enough. • This type of sampling is most useful for pilot testing.
- 15. Judgmental sampling or Purposive sampling The researcher chooses the sample based on who they think would be appropriate for the study. This is used primarily when there is a limited number of people that have expertise in the area being researched
- 16. • The use of sampling methods is a function of the nature of the population and the study coupled with such other functions like the dexterity of the researcher, and timing for the study alongside availability of resources/finance. • For purposes of clarity and better understanding, the determination of the sample size should be guided by ability to apply the method/approach being applied. Students should not be compelled to use Taro Yamane’s formular at all cost
- 17. THANK YOU