In this example, we might wish to first divide our sampling frame into two lists: weekend days and weekdays. a. Convenience c. Purposive d. Quota 17. In contrast, the stratified sampling process (and its simpler form as a simple random sample) is only subject to one level of chance from the selection of elements within each stratum, which will often improve the precision of an estimate made from the sample. If we took the 500 people attending a school in New York City, divided them by gender, and then took a random sample of the males and a random sampling of the females, the variable on which we would divide the population is called the _____. Did you know that Homework Lab is a student task sharing platform? They both are good, but for different purposes. In order to achieve generalizability, a core principle of probability sampling is that all elements in the researcher’s sampling frame have an equal chance of being selected for inclusion in the study. Although you think you can select things at random, human-generated randomness is actually quite predictable, as it falls into patterns called heuristics. a. ��d�� � [Content_Types].xml �(� ��MO�@��&��f��.x0�P1��Na�~ew@��N)4F���&�̼�3����Ӛl 1i� You can work on tasks on your own or ask professional Geeks for help. 14.1 Unobtrusive research: What is it and when should it be used? I suggest using Random.org, which contains a random number generator that can also randomize lists of participants. A number calculated with complete population data and quantifies a characteristic of the population is called which of the following? However, cluster sampling samples elements from only selected clusters, where stratified sampling selects a sample of at least one element from every stratum. f?��3-���]�Tꓸ2�j)�,l0/%��b� In this sampling strategy, already existing members of the sample provide referrals for new subjects. While the latter two strategies may be used by quantitative researchers from time to time, they are more typically employed in qualitative research. Sampling b. Census c. Survey research d. None of the above 25. ❌ Disadvantages of simple random sampling: This sampling strategy is similar to the simple random sampling, but there’s some system to it — starting number and interval. Clusters are selected for sampling, and all or some elements from selected clusters comprise the sample. As a result, in cluster sampling, the selection process is subject to two levels of chance variation, one for the selection of clusters and one for the selection of elements within a cluster. Which of the following is the most efficient random sampling technique discussed in your chapter? Kogan, S. M., Wejnert, C., Chen, Y., Brody, G. H., & Slater, L. M. (2011). c. Numbering all the elements of a sampling frame and then using a random number table to pick cases from the table. For instance, Chi-square test is typically applied to test whether two variables are related or not in qualitative research and you are welcome to check a, Non-probability sampling strategies for qualitative research, Probability sampling strategies for quantitative research, Usually takes little time to collect the data because you won’t need to spend additional time searching suitable members of the sample, Ideal if you want to conduct several interviews or observations, You can’t be sure if the sample is representative, Researcher’s bias can influence the results of the study, Quite quick to find members of the sample – people usually agree if they are asked by someone they know, Chances are, you’ll be able to find as many members as you need for research, Researcher’s bias – the margin of error exists because the choice of members of the sample depends on the researcher, Some people are likely to be reluctant about participating in a research even if asked to by someone they know, Allows the researcher to interact with the target audience directly, Requires considerable preparation for the researcher, Convenient, because enables the researcher to structure and categorize the data, The process of sample member selection is not random – researcher’s bias persists, Ensures a high degree of representativeness, which is exactly what we want from a statistical sample, Researcher’s bias is removed – the sampling process is fair because every member of the population can be picked randomly, Simple to conduct even with minimal knowledge, The sample size isn’t limited – the researcher can choose the sample size freely from the population, Can be expensive because it involves tedious data collection and creating lists of population members, Time-consuming and requires attention to detail, Might be difficult to collect all the necessary data, Ensures a high degree of representativeness, No need to use the table of random numbers, like in simple random sampling, Provides even distribution of population members in a sample, If there’s a hidden pattern in the population, there’s a risk that the systematic random sampling strategy will be affected by it, Can be time-consuming if the population is large, Can help find a more accurate answer to the research question than simple random sampling, because groups are selected accurately, Highly representative of all groups of the population, Can be expensive, because requires processing a large amount of data, Can’t be applied to a population where strata overlap, Easy and convenient, because many clusters are left out, Inexpensive and takes little time, as a rule, By leaving a considerable part of the population unrepresented, the researcher faces the risk of sampling error, which means that the chosen sample won’t reflect the whole population. 178), how many participants will you need for a research study with a population of 120,000? For that, you need probability sampling, which we will discuss in the next section. Since weekends make up less than a third of an entire week, there’s a chance that a simple random or systematic strategy would not yield sufficient weekend observation days. If you are unfamiliar with this concept, k is your selection interval or the distance between the elements you select for inclusion in your study. 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. This method is typically used when natural groups exist in the population (e.g., schools or counties) or when obtaining a list of all … We care about a potential participant’s likelihood of being selected for the sample because in most cases, researchers use probability sampling techniques to identify a representative sample from which to collect data.
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