Sampling involves the selection of a particular sample or group to represent an entire population. Sampling techniques are categorized into two major groups that comprise non-probability and probability sampling. In probability sampling, each member has a known and fixed opportunity to join the sample group. In the non-probability approach, the sample specimen has no certain probability of including an individual in the sample. Besides, the fundamentals of selection in the non-probability technique are absolute, whereas in the probability method are random. In non-probability sampling, the results generated are more/less biased, while in probability sampling, the outcomes generated are unbiased. While the non-probability method depends on the presumption that samples are uniformly disseminated within the entire population, probability sampling relied on principles of randomization where each entity acquires a fair opportunity for selection. Both sampling techniques show several similarities between them. There is a common tradition designed to generate a sample that can solely answer research questions. The traditional practice includes generalizing issues to an external population or situation for extrinsic validity. Biasness can influence sampling techniques from choosing a population unintentionally to excluding significant respondents to having sample sizes that accurately represent the entire population. Non-response bias happens when respondents withhold critical information intentionally and decide whether to participate or not. Suppose the sampling method allows participants to opt out or in, may generate underrepresented samples or include members without knowledge of the research topic. Sampling bias happens when some respondents have a higher probability of being selected than others. Sampling bias restricts the generalization of results since it excludes some aspects, thus threatening population validity. Therefore, results from biased samples generalize populations that have common characteristics with the selected model. The sampling plan will include a population above 18 years old involving members selected based on gender, age, ethnicity, education, party registration, and individuals with a history of marijuana use. The target population will aim at diversifying the results obtained from the various selected samples. Non-probability sampling would be appropriate in taking field polls for the legalization of marijuana. Heterogeneity sampling includes all views or opinions from the selected model without representing the views proportionately. California State first took a field sample before the legalization of marijuana to observe people's perspectives about the drug. In this case, heterogeneity sampling is appropriate for diversity and obtaining a comprehensive spectrum of views without identifying modal or average ideas. The selected sample will involve a thousand individuals representing all aspects, including ethnicity, age, education, party registration, area, and marijuana use. The sampling will use two processes; first, respondents will be recruited using mobile phones from random phone numbers obtained from the population. Respondents who will pass the screening questions will then receive an online survey link via email or SMS. Conducting an online survey will enable samplers to reach the participants quickly and avoid unnecessary conduct and crowding. An online survey has provided a faster method of assessing sampling members and collecting research data. However, the online survey has several drawbacks, including the inability to evaluate challenging populations, survey fraud, and the absence of interviewers (Andrade, 2020; Yu et al., 2020). Therefore, every sampler should regard online surveys as tentative when distributed to unfamiliar audiences and survey frauds. Nonetheless, if the online sampling is deployed individually to all participants, the sampler can conclude the number of participants reached. Samplers can presume that perspectives provided by the respondents are similar to most of the population's views if not all. Distributing the online survey in person offers the best scenario; the sampler can describe the population and sample, and the respondents are probably representative of the entire population (Andrade, 2020). However, if few members respond, the results might be contaminated, rendering them untrustworthy.
References
Andrade, C. (2020). The limitations of online surveys. Indian Journal of Psychological Medicine , 42 (6), 575–576. https://doi.org/10.1177/0253717620957496
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Yu, B., Chen, X., Chen, X., & Yan, H. (2020). Marijuana legalization and historical trends in marijuana use among US residents aged 12–25: Results from the 1979–2016 National Survey on drug use and health. BMC Public Health , 20 (1). https://doi.org/10.1186/s12889-020-8253-4
