POLI 343 Introduction to Political Research Session 12: Non-Probability Sampling Lecturer: Prof. A. Essuman-Johnson, Dept. of Political Science Contact Information: aessuman-johnson@ug.edu.gh College of Education School of Continuing and Distance Education 2014/2015 – 2016/2017 godsonug.wordpress.com/blog
What is Non-Probability Sampling? In non-probability sampling the researcher has no way of measuring the amount of error in the sample. The difference between non-probability and probability sampling is that non-probability sampling does not involve random selection and probability sampling does. Does that mean that non-probability samples are not representative of the population? Not necessarily. But it does mean that non-probability samples cannot depend upon the rationale of probability theory. Slide 2 Poli 343: Introduction to Political Research
Non- ProďaďilitLJ SaŵpliŶg ;CoŶt’d: At least with a probabilistic sample, we know the odds or probability that we have represented the population well. We are able to estimate confidence intervals for the statistic. With non-probability samples, we may or may not represent the population well, and it will often be hard for us to know how well we've done so. In general, researchers prefer probabilistic or random sampling methods over non-probabilistic ones, and consider them to be more accurate and rigorous. Slide 3 Poli 343: Introduction to Political Research
Non-Probability Sampling Types However, in applied social research there may be circumstances where it is not feasible, practicable theoretically sensible to do random sampling. Here, we consider a wide range of non-probabilistic alternatives. We can divide non-probability sampling methods into two broad types: accidental or convenience and purposive or quota . Most sampling methods are purposive in nature because we usually approach the sampling problem with a specific plan in mind. The most important distinctions among these types of sampling methods are the ones between the different types of purposive sampling approaches. Slide 4 Poli 343: Introduction to Political Research
Convenience/Accidental Sampling The most commonly used sampling method in behavioral science research is probably convenience or accidental sampling. In this type of sampling, the researcher simply uses as participants those individuals who are easy to get. People are selected on the basis of their availability and willingness to respond. Slide 5 Poli 343: Introduction to Political Research
Examples of Convenience/Accidental Sampling Examples include people on the street or in the shopping mall who are stopped and interviewed, people who respond to magazine or television survey or to an advertisement for a study in the newspaper. A researcher at the University of Ghana who wants the opinion of students would usually use the students in his class. Slide 6 Poli 343: Introduction to Political Research
Demerits of Convenience/Accidental Sampling Convenience sampling is considered as a weak form of sampling because the researcher makes no attempt to know the population or to use a random process in selection. The researcher has no control over the representativeness of the sample. Slide 7 Poli 343: Introduction to Political Research
Merits of Convenience/Accidental Sampling Despite this drawback, convenience sampling is probably used more often than any other kind of sampling. It is an easier, less expensive, more timely technique than the probability sampling techniques which involves identifying every individual in the population and using a laborious random process to select participants. Finally although convenience sampling offers no guarantees of representative and unbiased sample, we do not have to automatically conclude that this type of sampling is hopelessly flawed. Slide 8 Poli 343: Introduction to Political Research
Strategies to correct problems of Convenience/Accidental Sampling Most researchers use three strategies to help correct most of the serious problems associated with convenience sampling. First , researchers try to ensure that their samples are reasonable representative and not strongly biased. For example a researcher may select a sample that consists of Introduction to Politics students from the University of Ghana. If the researcher is careful to select a broad cross- section of students (males & females, different ages, different course levels etc) it is sensible to expect this sample to be reasonably similar to any other sample of University students around the country. Slide 9 Poli 343: Introduction to Political Research
Strategies to correct problems of Convenience/Accidental SaŵpliŶg ;CoŶt’d: Unless the research involves some special skill, it usually is reasonable to assume that a sample from one location is just as representative as a sample from any other Ghanaian University. The students in one state University in Accra are probably quite similar to other students in a state University in Cape Coast or Kumasi. The exception to this concept occurs whenever a convenience sample is obtained from a location with unusual or unique characteristics such as students from private universities. Slide 10 Poli 343: Introduction to Political Research
Strategies to correct problems of CoŶǀeŶieŶĐe/AĐĐideŶtal SaŵpliŶg ;CoŶt’d: The second strategy that helps to minimize potential problems with convenience sampling is simply to provide a clear description of how the sample was obtained and who the participants are. For example, a researcher might report that a sample of 100 students 966 females and 33 males all aged between 18 and 22 was obtained from an Introduction to Politics class from the University of Ghana. Such a sample may not be a perfect representative of the larger population at least everyone knows what the sample looks like and can make their own judgment about representativeness. Slide 11 Poli 343: Introduction to Political Research
Strategies to correct problems of CoŶǀeŶieŶĐe/AĐĐideŶtal SaŵpliŶg ;CoŶt’d: The third method for controlling the composition of a convenience sample is to use the same techniques that are used for stratified samples and for proportionate stratified samples. For example a researcher can ensure that boys and girls are equally represented in a sample of 30 preschool children by establishing quotas for the number of individuals to be selected from each subgroup. In this example rather than simply taking the first 30 children regardless of gender, who agree to participate, you impose a quota of 15 boys and 15 girls. This is called quota sampling. Slide 12 Poli 343: Introduction to Political Research
Purposive Sampling In purposive sampling, we sample with a purpose in mind. We usually would have one or more specific predefined groups we are seeking. For instance, have you ever run into people in a mall or on the street who are carrying a clipboard and who are stopping various people and asking if they could interview them? Most likely they are conducting a purposive sample (and most likely they are engaged in market research). They might be looking for Akan females between 30-40 years old. Slide 13 Poli 343: Introduction to Political Research
Purposiǀe SaŵpliŶg ;CoŶt’d: With a purposive sample, you are likely to get the opinions of your target population, but you are also likely to overweight subgroups in your population that are more readily accessible. All of the methods that follow can be considered sub-categories of purposive sampling methods. We might sample for specific groups or types of people as in modal instance, expert, or quota sampling. We might sample for diversity as in heterogeneity sampling. Or, we might capitalize on informal social networks to identify specific respondents who are hard to locate otherwise, as in snowball sampling. In all of these methods we know what we want -- we are sampling with a purpose. Slide 14 Poli 343: Introduction to Political Research
Sub-categories of Purposive Sampling Modal Instance Sampling In statistics, the mode is the most frequently occurring value in a distribution. In sampling, when we do a modal instance sample, we are sampling the most frequent case, or the "typical" case. In a lot of informal public opinion polls, for instance, they interview a "typical" voter. There are a number of problems with this sampling approach. First, how do we know what the "typical" or "modal" case is? We could say that the modal voter is a person who is of average age, educational level, and income in the population. Slide 15 Poli 343: Introduction to Political Research
Modal IŶstaŶĐe SaŵpliŶg ;CoŶt’d: But, it's not clear that using the averages of these is the fairest (consider the skewed distribution of income, for instance). And, how do you know that those three variables -- age, education, income -- are the only or even the most relevant for classifying the typical voter? What if religion or ethnicity is an important discriminator? Clearly, modal instance sampling is only sensible for informal sampling contexts. Slide 16 Poli 343: Introduction to Political Research
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