Discussion:
DQ1
Purposive sampling represents the best strategy for selecting research participants. In regards to social and behavioral sciences, this particular sampling technique denotes specificity in the selection of certain units or cases (Teddlie & Yu, 2007). This nonprobability type of sampling demands a level of control that can be categorized relative to various techniques and strategies. Purposive sampling is also applicability to wide range of research purpose (Teddlie & Yu, 2007). This wide range of purpose includes conducting extreme or deviant cases sampling-outlier sampling.
Purposive Sampling Strategies
There are three broad categories that depict the techniques associated with purposive sampling. These purposive sampling techniques are also relative to specific types of strategies-representativeness or comparability, special or unique cases, and sequential sampling (Teddlie & Yu, 2007). Firstly, representativeness or comparability is facilitated by analyzing different types of cases or selecting a sample to closely depicts a broader group of cases (Teddlie & Yu, 2007). Secondly, investigating special or unique cases involve a group of cases that are pertinent to the inquiry (Teddlie & Yu, 2007). Thirdly, sequential sampling denotes gradual selection principles that are used when the goal is to generate theory or define themes as the data is being collected (Teddlie & Yu, 2007).
Observation as a Data Collection Method
There are specific data collection methods relative to a qualitative or quantitative research. Depending on the nature of the research, it is important to first decide on the appropriateness of the collection method relative to the research question(s) (Burkholder, Cox, & Crawford, 2016). Futhermore, the order in which different types of data are collected must also be determined. Observation is a significant method of data collection. Typically, this approach to data collection denotes an attempt to make sense of an ongoing process that cannot be predicted (Babbie, 2017). Hence, to an extent, observation depicts an alternation between inductive and deductive inquiry.
Strengths. There are key strengths associated with observation as a primary data collection method. Firstly, this approach provides researchers with the most comprehensive perspective of a social phenomenon (Babbie, 2017). Secondly, observation affords a deeper understanding of a subject, including various nuances-behaviors and attitudes. Lastly, using observation as a method of collecting data allows researchers to study a subject within their natural environment (Babbie, 2017). In essence, observation provides contexts that may be missed, using other methods of data collection.
Limitations. Collecting data through an observatory method also has shortcomings. One of the limitations associated with observation is reactivity-observer effect. This concept depicts reactions-subjects altering behavioral patterns-within the social process (Babbie, 2017). Another limitation associated with observation is that data collected via this method is typically subjected to filtering and interpretation. In terms of replicating the research, data that are filtered during collection have inherent challenges. Also, because human behavior is not static, there are often transferability issues associated with observation as a data collecting method.
Ethical Implications
There are potential ethical issues that must be considered, when using observation as a data collection method. For example, analyzing the study habits of children from families that receive public assistance poses some ethical challenges. In order to mitigate against potential ethical violations, parents or guardians must consent to their children participating in the research. However, the quality of the study may also be impacted, because of the type of activity and the data collecting method.
Reliability and Validity
Understanding the relationship between reliability and validity measurement is crucial in public administration. Data and methodological consistency (reliability) increases the likelihood that the interpretation of the data has validity (Burkholder, et al., 2016). The method applied to data collection can also impact the reliability and validity of the inquiry. Reliability denotes that a measurement can be applied repeatedly to the same object, under different conditions, yielding the same result each time (Drost, 2016). In this context, validity of data implies that a measurement accurately depicts the real meaning of the intended concept. Therefore, using observation to collect data on the study habits of children from families that receive public assistance will not produce consistent (reliable) findings. However, this observation can be used as part of the data set.
References:
Babbie, E. (2017). The basics of social research (7th. Ed). Boston, MA: Cengage.
Burkholder, G.J., Cox, K.A., & Crawford, L.M. (2016). The Scholar-Practitioner's Guide to Research Design, 1st Edition. [MBS Direct].
Drost,E. A. (20..). Validity and reliability in social science research. Education Research and Perspectives 38(1), 105-124.
Onwuegbuzie, A. J., & Collins, K. M. (2007). A typology of mixed methods sampling designs in social science research. The Qualitative Report, 12(2), 281-316.
Teddlie, C. & Yu, F. (2007). Mixed methods sampling: A typology with examples. Journal of Mixed Methods Research 1(1), 77. DOI: 1177/2345678906292430.
DQ2
Probability sampling is the best strategy for testing using random selection (Yu, F. 2007). In probability sampling, each population member has a known, non-zero chance of participating in the study. In my view, the point of the sample should be random so that no bias of responses can occur. Randomization and luck is the core of probability sampling technique (Yu, F. 2007). Probability sampling is broken into four stages Identifying an appropriate sampling frame based on your research question objectives, determining suitable sample size, choosing the most appropriate sampling technique and selecting the samples, checking if the example is representative of the population Collins, (K. M. 2007). Surveys are an excellent method of data collection because surveys can solicit information from people. The downfall though of surveys is the response rate because it is a crucial survey parameter. If people are not answering the surveys, then the data will not be available for study. Lastly, validity is a judgment based on various types of evidence. The relevant evidence includes the measure's reliability, whether it covers the construct of interest, and whether the scores it produces are correlated with other variables they are expected to be associated with and not connected with variables that are conceptually distinct (Drost, E. A. 2011).
Teddlie, C., & Yu, F. (2007). Mixed methods sampling: A typology with examples. Journal of Mixed Methods Research,
Drost, E. A. (2011). Validity and reliability in social science research. Education Research and Perspectives, 38(1), 105-124.
Onwuegbuzie, A. J., & Collins, K. M. (2007). A Typology of Mixed Methods Sampling Designs in Social Science Research . The Qualitative Report, 12(2), 281-316.