Nursing Research: Reading Using, and Creating Evidence
Question
Directions
Discussions are designed to promote dialogue between faculty and students, and students and their peers. In discussions students:
Demonstrate understanding of concepts for the week
Integrate outside scholarly sources when required
Engage in meaningful dialogue with classmates and/or instructor
Express opinions clearly and logically, in a professional manner
Use the rubric on this page as you compose your answers.
Best Practices include:
Participation early in the week is encouraged to stimulate meaningful discussion among classmates and instructor.
Enter the discussion often during the week to read and learn from posts.
Select different classmates for your reply each week.
Discussion Questions
Data analysis is key for discovering credible findings from implementing nursing studies. Discussion and conclusions can be made about the meaning of the findings from the data analysis.
Share what you learned about descriptive analysis (statistics), inferential analysis (statistics), and qualitative analysis of data; include something that you learned that was interesting to you and your thoughts on why data analysis is necessary for discovering credible findings for nursing.
Compare clinical significance and statistical significance; include which one is more meaningful to you when considering application of findings to nursing practice.
Title: Nursing Research: Reading, Using and Creating Evidence
Edition: 4
Authors: Janet Houser
Publisher: Jones & Bartlett Learning
APA Citation
Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Jones & Bartlett.BOOK :


Solution
Nursing
Research: Reading Using, and Creating Evidence
An inferential analysis is the generalization
of the results obtained from the representative samples to correspond to the
population from which the sample was drawn (Wyllys, 2018). In most instances,
inferential is needed if the sample is randomly obtained with a promisingly
high response rate. A medical example of inferential analysis concludes that
drug abuse is common among the youth after randomly identified youths proved to
be drug abusers.
Descriptive analysis is a variety of
analyses that describe a given data and summarize the identified data
strategically to reveal the trends that may emerge from the data to meet the
data requirements (Bhat, 2019). A medical example of descriptive analysis is
identifying that all the participants are not affected in given research about
cancer.
Qualitative data analysis identifies
and interprets identified patterns and trends in textual data to identify their
relationship with the issue of concern (Bhat, 2019). A medical example of
qualitative data analysis is the observed shingles in patients affected with
"herpes zoster".
Lesson learned on the importance of data analysis.
Data analysis is significant in
determining credible findings as it helps avoid biases by statistical treatment
assistance (Michael, 2020). In research, correct findings are deterred by bias
identification, and therefore a correct analysis prevents biases that translate
to accurate findings.
Statistical significance refers to
the realness or the faultiness of the differences within the study groups.
Clinical significance is a term used to refer to a course where the provided
treatment had significant effects and genuine effects. Statistical significance
is mainly assigned to naturally occurring results rather than those that occur
by chance (Matt,
2018). Clinical significance largely depends on statistical significance
due to the computation of the p-values and the significance level. Clinical
significance is more meaningful when considering findings in the nursing
practice application.
References
Bhat, A. (2019, June
25). Data analysis in research: Why data,
types of data, data analysis in qualitative and quantitative research |
QuestionPro. QuestionPro. https://www.questionpro.com/blog/data-analysis-in-research/
Matt. (2018). Clinical Significance vs. Statistical
Significance - Side-by-Side Comparison. Mhaonline.
https://www.mhaonline.com/faq/clinical-vs-statistical-significance
Michael. (2020, October
19). Importance of Data Analysis in
experimentation paraphrase Calculator.
https://paraphrase.projecttopics.org/importance-of-data-analysis-in-a-research-paper.html
Wyllys, R. E. (2018). Teaching descriptive and inferential
statistics in library schools. Journal
of Education for Librarianship, 3-20.




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