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23 hours ago, at 7:46 PM
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In my research I am conducting quantitative analysis, the advantages of inferential analysis and qualitative analysis are that; inferential analysis, helps one in drawing a conclusion based on specific explorations and helps in suggestions of explanations. This is also similar to qualitative analysis. It advocates for predictive qualities; in this, people can analyze some issues when it happens. They can draw a conclusion based on the available data (Tappen, 2015). Inferential analysis usually uses a comparison between different groups and using the comparison of the larger group. It concludes this is also similar to qualitative analysis as information is drawn from the available data when the research team has gathered information and realizes that it only comes from a small group, collecting data changes.
The disadvantages of both inferential analysis and qualitative analysis include; Inferential analysis is based on the concept that using values that are developed in a sample to be used to measure in a given population there will exist a problem as they will be inaccurate data that provides wrong information of a population that has not been measured and qualitative analysis it does not provide a statistical representation of data, it only provides data from a perspective point of view not the actual data from the population. Another disadvantage in both is that in inferential analysis, the researcher makes guesses based on theories. This again shows that they will exist some uncertainty in the process which will have some impacts on the results of qualitative analysis. The results are also based on individual perspectives.
Reference
Ruth M. Tappen. (2015). Nursing Research. Advanced Nursing Research: From Theory to Practice. (2nd ed.). ISBN-13: 9781284048308. ISBN-10: 1284048306. Publisher: Jones & Bartlett Learning
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Joscelyne Lastra
7/21/21, 5:23 PM
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Joscelyne Lastra
Nursing Research
Professor Dr. Barry Graham
Discussion Week 12
Inferential Analysis & Analysis of Qualitative Data
The present research about the incidence and prevalence of eating disorders in young population of Latin community use the analysis of qualitative and quantitative analysis. Through the collection and statistical analysis of responses from the sample and subgroups, it is possible to develop the estimation of bivariate association in order to calculate the correlation between the ethnical groups and the prevalence of the disorders. As the term of bivariate effect defines in the relationship between the variables a positive correlation (under the regression calculation) would reinforce the research question validity of the manifestation of eating disorder within the Latin females at the same level of the most recognized group of Caucasians. Similarly, in terms of inference analysis, the correlation will ensure additional estimations over the subgroups.
However, the research also includes estimation calculation according to the qualitative data of the research. For one side, it is necessary to review the content analysis from the open-question of the interviews in order to capture the subject´s interpretation of any impressionistic, intuitive, interpretive analysis in systematic with the purpose of adding more elements for the interpretation of researchers (Tappen, 2016). Moreover, the nature of the research considers highly relevant the use of ethnographic analysis when such variable (ethnicity and cultural background) for the proper understanding of the culture over the manifestation of eating disorders. Under the assumption that an ethnography is related to the culture, it is important to determine how culture influence over the beliefs, norms, and values of the patient in relation to the structure and function of the assimilation and acculturation.
The inferential analysis can deliver among its advantages the detailed information provision (more over the descriptive statistics) and the definition of relationships between the variables. In addition, it serves to reveal the cause-effect phenomena and to estimate predictive results while it supports the data to sustain any tested theory (Blaikie, 2018). Still, it is necessary to mention at the downside that it may quite difficult for the application and its use while it induces certain risks about the misuse and abuse from the researcher´s implication of the data set. From the qualitative analysis, it is important to mention the chance of content generation, the provision of insights for the specific research, and the creativity as the driving force. Moreover, the qualitative data is oriented to the open-ended analysis where it is incorporate the human experience with a high level of flexibility (Stevenson, 2018). However, in the case of disadvantages, the qualitative data is more difficult to be processed in term of statistics because it requires a more experience as well as the demand of multiple sessions and the complications in the replication of the results.
References
Blaikie, N. (2018). Inferential analysis: from sample to population. In Blaikie, N. Analyzing quantitative data (pp. 159-213). London: SAGE Pub. doi: 10.3705/9872476807604
Stevenson, S. (2018.). Qualitative research: Grounded theory: what is it? Retrieved November 17, 2020, from https://guides.temple.edu/c.php?g=77914
Tappen, R. M. (2016). Advanced nursing research: From theory and practice (2nd ed.). Burlington, MA: Jones & Bartlett Learning.
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Sinai Penalver
7/21/21, 2:57 PM
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For my research studies, I took a qualitative analysis approach as the study examines theoretical opinions of how nurses encounter certain leadership and management challenges and potential solutions for these challenges, and the strategic importance of addressing those problems. The research relies primarily on printed documents to get vital information, as a result, descriptive research such as survey research will be used for the purpose of this study to gain the actual challenges faced by nurses. This descriptive research, therefore, will be important since it will provide adequate opportunities to gather data mainly in case there is limited available information for the studied subject. Therefore, using qualitative analysis can allow the researcher to take a flexible approach and explain something statistical numbers may not reveal. Additionally, this form of approach can be cost-efficient as it utilizes available data already established. Unfortunately, this form of analysis can also lead to bias which is a key feature a researcher must address and/or control for during the research design. Another disadvantage to consider is that in the future, it may be difficult to replicate results. The inferential analysis takes a more statistical approach as it considers various forms of statistical tests such as T-Tests, ANOVA, and ANCOVA. This form of analysis can be beneficial to the researcher as it provides detailed information on descriptive statistics, gives insight into the relationship or association between the variables of the research, and generates causes and effects of a relationship to yield predictions. On the contrary, this style of research analysis can be difficult to learn as the researcher must determine which test to run and why giving room for error. Overall, both forms of analysis give great insight to a research study, but one must account for the disadvantages in order to develop the best outcome.
References
Tappen, R. M. (2016). Inferential Analysis. In Advanced nursing research: from theory to practice (pp. 355 394). Essay, Jones & Bartlett Learning.
Tappen, R. M. (2016). Analysis of Qualitative Data. In Advanced nursing research: from theory to practice (pp. 395 – 430). Essay, Jones & Bartlett Learning.
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Inferential Analysis, Analysis of Qualitative Data
RUBRIC |
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Excellent Quality 95-100%
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Introduction
45-41 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Literature Support 91-84 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Methodology 58-53 points Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met. |
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Average Score 50-85% |
40-38 points More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided. |
83-76 points Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration. |
52-49 points Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met. |
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Poor Quality 0-45% |
37-1 points The background and/or significance are missing. No search history information is provided. |
75-1 points Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration. |
48-1 points There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met |
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Inferential Analysis, Analysis of Qualitative Data