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    the ____________ is the non-random sampling technique wherein the choice of sample items depends exclusively on the investigator’s knowledge.

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    Judgmental Sampling: Definition, Examples and Advantages

    Judgmental sampling, also called purposive sampling or authoritative sampling, is a non-probability sampling technique in which the sample members are chosen only on the basis of the researcher's knowledge and judgment. Learn about its definition, examples, and advantages so that a marketer can select the right sampling method for research.

    Judgmental Sampling: Definition, Examples and Advantages

    Judgmental Sampling Definition

    Judgmental sampling, also called purposive sampling or authoritative sampling, is a non-probability sampling technique in which the sample members are chosen only on the basis of the researcher’s knowledge and judgment. As the researcher’s knowledge is instrumental in creating a sample in this sampling technique, there are chances that the results obtained will be highly accurate with a minimum margin of error.

    The process of selecting a sample using judgmental sampling involves the researchers carefully picking and choosing each individual to be a part of the sample. The researcher’s knowledge is primary in this sampling process as the members of the sample are not randomly chosen.

    Select your respondents

    When to execute Judgmental Sampling?

    Judgmental sampling is most effective in situations where there are only a restricted number of people in a population who own qualities that a researcher expects from the target population. Researchers prefer to implement Judgmental sampling when they feel that other sampling techniques will consume more time and that they have confidence in their knowledge to select a sample for conducting research.

    Judgmental or Expert sampling is usually used in situations where the target population comprises of highly intellectual individuals who cannot be chosen by using any other probability or non-probability sampling technique. It is also used in situations where the sample selected using other sampling methods need to be approved or filtered. For instance, in situations where a researcher conducts convenience sampling to gather feedback from professors about their university but the fact that there are high chances of the results to be skewed, researchers prefer judgmental sampling to select those professors who will provide 100% feedback about the university.

    Selecting each individual of the sample is a critical challenge that an intellectual researcher will undertake. It is a tedious task to handpick members of a sample while ensuring there is no bias involved.

    The authority involved in the selection process may not necessarily be “experts” in the field but they have to comply with certain characteristics expected from a Judgmental sampling authority. Education or work experience is not considered while appointing authorities for the selection process.

    Purposive sampling is used where there is time-constraint for sample creation and the authorities involved would prefer relying on their knowledge and not on other sampling methods. But, one must keep in mind, the fact that a researcher may or may not have the appropriate proficiency to conduct an effective sampling process. This is the only disadvantage of purposive sampling. Each researcher who takes up the responsibility of creating a sample using expert sampling will have to be extremely confident in their own skills and understanding of the subject.

    Examples of Judgmental Sampling

    Here are two distinct Judgmental Sampling examples:

    Consider a scenario where a panel decides to understand what are the factors which lead a person to select ethical hacking as a profession. Ethical hacking is a skill which has been recently attracting youth. More and more people are selecting it as a profession. The researchers who understand what ethical hacking is will be able to decide who should form the sample to learn about it as a profession. That is when judgmental sampling is implemented. Researchers can easily filter out those participants who can be eligible to be a part of the research sample.

    There are many tribes in the world which have their own religious beliefs, for instance, the Balinese people follow syncretism, which is considered to be a mixture of  Hinduism and Buddhism. For researchers who plan to study the culture of Southeast Asian countries, it is advised that they select strata using judgmental sampling as religious beliefs are considered to be highly sensitive in this part of the world. Due to the sensitivity of the topic, if samples of those who have appropriate knowledge are created and research is conducted with those samples, results will be highly accurate. Probability sampling techniques often produce altered results in such cases.

    Judgmental Sampling Advantages

    Consumes minimum time for execution: In this sampling approach, researcher expertise is important and there are no other barriers involved due to which selecting a sample becomes extremely convenient.Allows researchers to approach their target market directly: There are no criteria involved in selecting a sample except for the researcher’s preferences. Due to this, he/she can communicate directly with the target audience of their choice and produce desired results.Almost real-time results: A quick poll or survey can be conducted with the sample using judgmental sampling since the members of the sample will possess appropriate knowledge and understanding of the subject. Select your respondents

    Read more about:

    Probability Sampling

    Non-probability Sampling

    Cluster Sampling

    Simple Random Sampling

    Stratified Random Sampling

    Systematic Sampling

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    The method of sampling, in which the choice of sample items depends exclusively on the judgement of the investigator is termed as ________. a) Convenience sampling b) Quota sampling c) Systematic sampling d) Judgement sampling

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    Question:

    The method of sampling, in which the choice of sample items depends exclusively on the judgement of the investigator is termed as _____.

    A. Convenience sampling

    B. Quota sampling

    C. Systematic sampling

    D. Judgement sampling

    Judgement Sampling

    In non probability sampling techniques, all elements do not have the same probability to get selected in the final consideration set which is also known as the sample. One of these techniques is judgement sampling, which is also known as purposive sampling. Judgement sampling method carries with it the researcher's bias, as a researcher might select candidates for the sample in a prejudice manner. The researcher is more likely to have an expertise relating to the chosen sample items.

    Answer and Explanation:

    The sampling technique described here is D. judgement sampling which is a non-probability sampling technique. It is not preferred by many researchers due to the reduction in external validity of the research, which uses judgement sampling.

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    What is Random Sampling? - Definition, Conditions & Measures

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    Chapter 7 / Lesson 2

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    Learn what random sampling is and understand its definition and types. Discover examples of random sampling and see how random sampling is useful in statistics.

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    Chapter 8 Sampling

    Chapter 8 Sampling

    Sampling is the statistical process of selecting a subset (called a “sample”) of a population of interest for purposes of making observations and statistical inferences about that population. Social science research is generally about inferring patterns of behaviors within specific populations. We cannot study entire populations because of feasibility and cost constraints, and hence, we must select a representative sample from the population of interest for observation and analysis. It is extremely important to choose a sample that is truly representative of the population so that the inferences derived from the sample can be generalized back to the population of interest. Improper and biased sampling is the primary reason for often divergent and erroneous inferences reported in opinion polls and exit polls conducted by different polling groups such as CNN/Gallup Poll, ABC, and CBS, prior to every U.S. Presidential elections.

    The Sampling Process

    Figure 8.1. The sampling process

    The sampling process comprises of several stage. The first stage is defining the target population. A population can be defined as all people or items ( unit of analysis ) with the characteristics that one wishes to study. The unit of analysis may be a person, group, organization, country, object, or any other entity that you wish to draw scientific inferences about. Sometimes the population is obvious. For example, if a manufacturer wants to determine whether finished goods manufactured at a production line meets certain quality requirements or must be scrapped and reworked, then the population consists of the entire set of finished goods manufactured at that production facility. At other times, the target population may be a little harder to understand. If you wish to identify the primary drivers of academic learning among high school students, then what is your target population: high school students, their teachers, school principals, or parents? The right answer in this case is high school students, because you are interested in their performance, not the performance of their teachers, parents, or schools. Likewise, if you wish to analyze the behavior of roulette wheels to identify biased wheels, your population of interest is not different observations from a single roulette wheel, but different roulette wheels (i.e., their behavior over an infinite set of wheels).

    The second step in the sampling process is to choose a sampling frame . This is an accessible section of the target population (usually a list with contact information) from where a sample can be drawn. If your target population is professional employees at work, because you cannot access all professional employees around the world, a more realistic sampling frame will be employee lists of one or two local companies that are willing to participate in your study. If your target population is organizations, then the Fortune 500 list of firms or the Standard & Poor’s (S&P) list of firms registered with the New York Stock exchange may be acceptable sampling frames.

    Note that sampling frames may not entirely be representative of the population at large, and if so, inferences derived by such a sample may not be generalizable to the population. For instance, if your target population is organizational employees at large (e.g., you wish to study employee self-esteem in this population) and your sampling frame is employees at automotive companies in the American Midwest, findings from such groups may not even be generalizable to the American workforce at large, let alone the global workplace. This is because the American auto industry has been under severe competitive pressures for the last 50 years and has seen numerous episodes of reorganization and downsizing, possibly resulting in low employee morale and self-esteem. Furthermore, the majority of the American workforce is employed in service industries or in small businesses, and not in automotive industry. Hence, a sample of American auto industry employees is not particularly representative of the American workforce. Likewise, the Fortune 500 list includes the 500 largest American enterprises, which is not representative of all American firms in general, most of which are medium and small-sized firms rather than large firms, and is therefore, a biased sampling frame. In contrast, the S&P list will allow you to select large, medium, and/or small companies, depending on whether you use the S&P large-cap, mid-cap, or small-cap lists, but includes publicly traded firms (and not private firms) and hence still biased. Also note that the population from which a sample is drawn may not necessarily be the same as the population about which we actually want information. For example, if a researcher wants to the success rate of a new “quit smoking” program, then the target population is the universe of smokers who had access to this program, which may be an unknown population. Hence, the researcher may sample patients arriving at a local medical facility for smoking cessation treatment, some of whom may not have had exposure to this particular “quit smoking” program, in which case, the sampling frame does not correspond to the population of interest.

    The last step in sampling is choosing a sample from the sampling frame using a well-defined sampling technique. Sampling techniques can be grouped into two broad categories: probability (random) sampling and non-probability sampling. Probability sampling is ideal if generalizability of results is important for your study, but there may be unique circumstances where non-probability sampling can also be justified. These techniques are discussed in the next two sections.

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