A basic one-stage design takes a simple random sample of clusters and selects for sampling all elements within those clusters, although this design is rarely used in practice. As a researcher, you might wish to understand how satisfaction varies across these two types of housing arrangements. In determining which probability sampling approach makes the most sense for your project, it helps to have a strong understanding of your population. In this example, we might wish to first divide our sampling frame into two lists: weekend days and weekdays. From there, you would sequentially assign a number to each fraternity member, or element, and then randomly select the elements from which you will collect data. This was the case for Steven Kogan and colleagues (Kogan, Wejnert, Chen, Brody, & Slater, 2011) [4] who wished to study the sexual behaviors of non-college-bound African American young adults who lived in high-poverty rural areas. 12.2 Pre-experimental and quasi-experimental design. a. Afterward, the researcher uses a lottery method or random numbers method to pick the members into a sample. Population c.  Statistic d.  Element 29. You probably know that college classes are different sizes. That would be a case of sampling error—a mismatch between the results of the sample and the true feelings of the overall class. They are both nonprobability methods, so we include them in this section of the chapter. This is another qualitative research sampling method. Cluster sampling is most often applied when the members of the community are spread out geographically – for instance, if you’re dealing with a whole state or country. A nonrandom sampling method b. ICC is typically interpreted as the correlation between the responses of individuals in the same cluster. While the latter two strategies may be used by quantitative researchers from time to time, they are more typically employed in qualitative research. Do you notice any problems with our selection of observation days in Table 1? �:RD��(�R�� ?��"I_�=~{:P$}�i�@vҙp��d"b�4�3�B��q��I���'�$+b �G�C �O%�܊�{'K�ok���~'��N.N/i�XA�7��J���� " That is, only a certain number of clusters (groups) is selected for research, and all the other clusters are unrepresented. This strength is common to all probability sampling approaches summarized in Table 10.4. Snowball sampling is an especially useful strategy when a researcher wishes to study a stigmatized group or behavior. Would that be a representative sample of all students in the class? Later, we’ll look more closely at the process of selecting research elements when drawing a nonprobability sample. The downside of this simple approach is that it results in differing sample sizes per cluster, making it less attractive than other designs. There is one clear instance in which systematic sampling should not be employed. The researcher can only yield perfect results if they include everyone from the target population into the sample, which defeats the purpose of sampling. The professor uses undergraduates at your school as their sampling frame. Systematic sampling techniques are somewhat less tedious but offer the benefits of a random sample. Stratified Random Sampling c. Systematic Sampling d. Cluster sampling 30. This method is typically used when natural groups exist in the population (e.g., schools or counties) or when obtaining a list of all population elements is impossible or impractically costly. Stratified sampling is a good technique to use when a subgroup of interest makes up a relatively small proportion of the overall sample, like in our previous example. Because elements within a cluster are often similar—a phenomenon called a cluster effect—it may be redundant and inefficient to sample a large proportion of the elements within a cluster. a. a. To draw a convenience sample, a researcher simply collects data from people or other relevant elements that they can access conveniently. Finally, convenience sampling is another nonprobability sampling strategy that is employed by both qualitative and quantitative researchers. Sampling b. Census c. Survey research d. None of the above 25. Here are the steps to perform cluster sampling: Sample: Decide the target audience and also the sample size. Researcher relies on participant referrals to recruit new participants. a. a. a. It is worthwhile to note that each stage is subject to its own sample error, so choosing to sampling in multiple stages could yield greater error. If you’re struggling with sampling strategy for your term paper or research paper, you can contact our Geeks by sharing your task or leaving a comment below – I’ll do my best to help you figure any sampling strategy out. Nonprobability sampling refers to sampling techniques for which a person’s likelihood of being selected for membership in the sample is unknown. That’s okay because generalizing to a larger population is not the goal with nonprobability samples or qualitative research. Using random selection does not mean that your sample will be perfect. a. Snowball sampling b. a. That said, this does not mean that nonprobability samples are drawn arbitrarily or without any specific purpose in mind (that would mean committing one of the errors of informal inquiry discussed in Chapter 1). Will you gather a lot of structured data or a small amount of unstructured data? Generalizability refers to the idea that a study’s results will tell us something about a group larger than the sample from which the findings were generated. Sampling with replacement c. Simple random sampling d. Systematic sampling 21. Let’s say, for example, that you wanted to observe campus binge drinking on different days of the week. At the same time, cluster sampling is generally less precise than simple random or stratified sampling; therefore, it is typically used when it is economically justified (i.e., when a dispersed population would be expensive to survey). Choosing volunteers from an introductory psychology class to participate b. Quota sampling c.  Purposive sampling d.  Random sampling 28. ���%�m�f�΁C��z���#@�Pw���� qFr�ğsgqk����`pr�b��ў��}����|yzl>�7����[���c�q�.�ܹ�뽏~����o��FRޢ�I�8���1,��Fn;�߿�7�w����^Ecs%}W��I�� /�b�� S���Sz|̛X����[��?*�2�/�L�"v��΍����#�̍R? 14.2 Strengths and weaknesses of unobtrusive research, 16.3 The uniqueness of the social work perspective on science. These include purposive samples, snowball samples, quota samples, and convenience samples. A researcher begins with specific characteristics in mind that they wish to examine and then they seek out research participants who cover that full range of characteristics. Which of the following will give a more “accurate” representation of the population from which a sample has been taken? N� R@ � word/_rels/document.xml.rels �(� ���N�0E�H�C�=qR���-���L"�#{���J�Be��r��{�f��l�e|���V �È� By all means, in a perfect world, we wouldn’t need to have samples and have access to the data about each item in the population, but the reality is that we need sampling. a. a. Or, even better, let’s become friends with it and start by communicating in simple terms. Table 10.3 shows a list of the population elements for this example. Probability samples usually require a real list of elements in your sampling frame, though cluster sampling can be conducted without one. Nevertheless, cluster sampling is a highly efficient method. Convenience sampling c. Quota sampling d. Purposive sampling e. They are all forms of nonrandom sampling 8. Did you know that Homework Lab is a student task sharing platform? Name lab. This means that clusters [Page 299]containing a greater size measure (e.g., the number of population elements) are more likely to be included in the sample than clusters with fewer elements. Which of the following statements are true? In a population, all subjects have at least one common characteristic. It is recommended to use the whole population rather than a sample when the population size is of what size? Which of the following would generally require the largest sample size? (ėI A type of sampling used in qualitative research that involves selecting cases that disconfirm the researcher's expectations and generalizations is referred to as _____. Designs with more than two stages may also be useful; a three-stage statewide survey, for example, could sample school districts, then schools within selected districts, then teachers within selected schools. Proportional stratified sampling b. This sampling strategy is suitable when you’re dealing with a heterogeneous population that has several groups in it (they don’t overlap, but together represent the population in its entirety). a. Clusters are selected for sampling, and all or some elements from selected clusters comprise the sample. 242 b. 12.1 Experimental design: What is it and when should it be used? There are several types of nonprobability samples that researchers use.