Problem Evaluation and Resolution Essay Example

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Reflective and Critical analysis of Mixed Research Methods

I have assessed and established that mixed methods in research is gaining a wider use owing to the synergies of using quantitative and qualitative methods. I appreciate the adherence to research ethics which is a valuable asset in increasing credibility of the study findings. I understand that for a research to hold any meaning to the respondents and analysts, it must conform to the norms of society. I believe that in my upcoming research proposal, I will require a good ethical orientation to ensure my proposal is error free, truthful and knowledgeable. I can acknowledge that ethics has application in upholding copyrights, patents, authorship and confidentiality. I think research requires logical and understanding and coherence for it to possess relevance, theory testing and accurate phenomena description.

I believe reflective learning and critical thinking are intertwined when it comes to using mixed methods. This has engendered greater application in engineering, social studies and medicine. I am now confident that mixed methods explores and compensates for the weaknesses of both quantitative and qualitative methods into multiple investigative dimensions. With mixed methods I am able to perceive the natural, contextualized and in-depth of research that would have reduced validity in qualitative measures and increase the predictive capability of quantitative measures.

I have learned that qualitative measures make attempts to explore people’s experiences around the world in real time. I can decipher the struggle by researchers to organize, interpret and analyze data meaningfully using focus groups, surveys and unstructured interviews. I now know that it can be applied to social work to enhance both academic and practical settings. I understand that there are four qualitative methods such as phenomenology, grounded theory, field research and ethnography. I will endeavor to apply one of these methods in my upcoming research. I now appreciate data collection as the most research means to obtain information in any project. In this regard, I believe any research requires high methodological standards and expert advice to provide accurate results and limit errors which is likely to uphold high data output quality.

I have learned the use of mixed methods to provide excellent analysis in the mix of qualitative and quantitative measures. I now understand that for a theory to be robust, it must be backed by cases studies, advice, experiments, practical exercises and templates. I confirm that mixed methods utilizes both inferential and descriptive statistics in a simultaneous manner. I believe analysis is about combining the descriptors, excerpts, resources and code tree to bring about a thorough analysis. I contend that descriptive statistics utilizes the measures of central tendency, analysis of variance (ANOVA), measures of dispersion and t-test. I have learned these quantitative measures provide factual and exact measurements while qualitative analysis determines perceptions and opinions. I am confident that qualitative means uses nominal and ordinal scales while quantitative uses interval and ratio scales.

I have learned the influence of triangulation as an approach to increase data validity. I understand this approach as using multiple approaches to investigate research questions in a bid to increase study confidence levels. I think that through triangulation, it is possible to establish checks and accurate reflection of the study situation. I believe that reflective and experiential learning are necessary in education research and training. In this learning case, I am confident that I will uncover deeper meaning of data and increase the relative strengths of qualitative research alongside the different approaches. I believe triangulation has increased use in bringing about the truth in any study area. I understand these measures are crucial in quantitative measures such as engineering, biotechnology and medicine. I can now tell that a single and empirical research has to uncover a relevant theory, exploit various data sources, make observations and establish the degree of convergence across the components. In this understanding, I believe it is possible to minimize data biasness.

I have a deeper understanding of reliability and validity in any research process. My understanding of reliability is the magnitude of a measure to give consistency of results even when repeated in different areas. I learned that validity and reliability exist in all the research processes. I know that reliability alone is not sufficient but necessary since it has to be valid; I think these measures reflect the study concept in mixed approaches since. Through this, I have learned that validity is about the extent at which a procedure. I think it offers a true measure of the variable. I learned that it attempts to eliminate the random systemic errors in the measurement. I believe that these measures have succeeded in fulfilling what it claims to solve in both quantitative and qualitative processes. I now know that validity is more important than reliability since reliable instruments can provide invalid results. When reliability and validity are accurate then the data establishes the precise measurements.

To crown it, I have learned hypothesis testing to be a process that allows for decision making based on data of controlled and observational experiments. I believe that null hypothesis can be countered by alternative hypothesis so as to bring about results that are statistically significant if established to have happened through chance alone. I can tell that there is a null hypothesis denoted by H0 and the alternative hypothesis denoted by H1which has to be proven. I know that given the confidence level (p) and the degrees of freedom (df), it is possible to establish relationships of variables.

I know that experimental research uses 99 percent confidence levels while social research can take up to 95 percent confidence levels. This is defined by the significance level which is the pre-determined probability. I learned that a statistically significant result is a positive result while a result under null hypothesis going beyond the significant level is a null result. I now tell that a common application is in lady tasting tea, clairvoyant card game, and courtroom trials. I believe hypothesis testing is important in establishing a theory based on proven facts.