NR 439 Week 6: Data Results and Analysis
Chamberlain University NR 439 Week 6: Data Results and Analysis– Step-By-Step Guide
This guide will demonstrate how to complete the Chamberlain University NR 439 Week 6: Data Results and Analysis assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.
How to Research and Prepare for NR 439 Week 6: Data Results and Analysis
Whether one passes or fails an academic assignment such as the Chamberlain University NR 439 Week 6: Data Results and Analysis depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.
After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.
How to Write the Introduction for NR 439 Week 6: Data Results and Analysis
The introduction for the Chamberlain University NR 439 Week 6: Data Results and Analysis is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.
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How to Write the Body for NR 439 Week 6: Data Results and Analysis
After the introduction, move into the main part of the NR 439 Week 6: Data Results and Analysis assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.
Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.
How to Write the Conclusion for NR 439 Week 6: Data Results and Analysis
After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.
How to Format the References List for NR 439 Week 6: Data Results and Analysis
The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.
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Sample Answer for NR 439 Week 6: Data Results and Analysis
According to this week’s lesson, the four basic rules for understanding results in a research study are understand the purpose of the study, identify the variables—dependent and independent, identify how the variables are measured, and look at the measures of central tendency and the measures of variability for the study variables. I chose to explore the rule: identify the variables-dependent and independent. A dependent variable is something that depends on other factors. An independent variable is a variable that stands alone and isn’t changed by the other variables you are trying to measure. A dependent factor can be changed by what happens with the independent factor but a dependent factor can never change an independent factor. A simple example would be: Insulin causes a drop in blood sugar. Insulin is the independent factor and blood sugar is the dependent factor. There is no way for blood sugar to cause a drop in insulin.
“Statistical significance tells us the findings are real; clinical significance tells us if the results are important for practice” (Houser, 2018, p. 356). Both statistical significance and clinical significance relate to quantitative data. Statistical significance could mean that in 0.5% of the population x, y, and z occurred. The probability of it happening could be chance because it is such a small percentage of the population. Clinical significance shows to what degree the new intervention is needed to make a difference in a client’s life. Clinical significance is thought to be much more meaningful but without the initial statistical significance, further studies would not have been done to prove a clinical significance. In reference to practice, clinical significance is more important when applying evidence to my practice. When utilizing clinical significance, there is evidence-based support of your actions.
“The goal of statistical inference is to estimate likely true or large-sample effects based on random samples from the collective(s) of interest” (Wilkinson & Winter, 2014, p. 492). In a study, the variances between groups are measured quantitatively and examined using inferential statistics. Inferential statistics utilize numbers to determine the probability that random error plays a role in the outcome. It also suggests that independent variables have an effect on the results. Descriptive statistics are usually related to the mean, minimum, maximum, standard deviation, and median of results. These studies are not usually utilized for change in evidence-based practice but are more likely to be used to measure current practice. An example of inferential statistics would be if I questioned all of the Emergency Department nurses at my facility about the effects of education on compassion fatigue. The results would infer that the results would be the same in another location but I only used a small population. For the descriptive statistics, I would use a table, graph, or chart in addition to the statistical data to summarize my study.
~Candee Crane
References:
Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.
Wilkinson, M., & Winter, E.M. (2014). Clinical and practical importance vs statistical significance: Limitations of conventional statistical inference. International Journal of Therapy & Rehabilitation, 21(10), 488-495.
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Sample Answer 2 for NR 439 Week 6: Data Results and Analysis
Discuss one of the four basic rules for understanding results in a research study.
According to CCN, 2017-week 6 lesson, the four basic rules for understanding results in a research study are: Understanding the purpose of the study, identify the variables- dependent and independent, identify how the variables are measured, and look at the measures of central tendency and the measures of variability for the study variables. My discussion will be focused on rule # 2 Identify the variables-dependent and independent. Business dictionary defines variable as a characteristic, number, or quantity that increases or decreases over time, or takes different values in different situations. There are two basic types of variables (1) Independent variable that can take different values and can cause corresponding changes in other variables, and (2) Dependent variable are those that can take different values only in response to an independent variable (businessdictionary.com). An example of a variable is patient’s vital signs. We can measure a patient’s vital signs, but they can increase or decrease.
Compare clinical significance and statistical significance. Which one is more meaningful when considering applying evidence to your practice?
Clinical significance is generally expected to reflect the extent to which an intervention can make a real difference in patients’ lives. Statistical significance is the comparison of differences to standard error and the calculation of the probability of error that gives inferential analysis its strength. Nevertheless, statistical significance is just one of the important measures that determine whether research is truly applicable to practice (Houser, 2018). Statistical significance is a requirement for using evidence in practice: If results are due to error, then their application is irrelevant. At the same time, statistical significance tells the nurse little about whether the results will have a real impact in patient care. (Houser, 2018).
Compare descriptive statistics and inferential statistics in research. Please give an example of each type that could be collected in a study that would be done on your nursing clinical issue you identified in previous week.
Descriptive statistics use numbers narratively, in tables, or in graphic displays to organize and describe the characteristics of a sample (Houser, 2018, p291). It uses data to provide descriptions of the population, either through numerical calculations or graphs or tables. Descriptive statistics are the characteristics that are given to the sample of a research study. Descriptive statistics tell us, who was in the study and what did the study show us about the hypothesis (CCN, 2018). An example of descriptive statistics is my research question: Will follow-up telephone call and visit by home health nurse 3 to 7 days post discharge help reduce the rate of hospital readmission for patients 65 years and above with CHF. The descriptive study for my research will be patients 65 years old and above with CHF.
Inferential statistics can help to make a general statement about the sample population and compare them with other populations. (Houser, 2018). It makes inferences and predictions about a population based on a sample of data taken from the population in question. Inferential statistics help answer the question. How strong is the evidence from the study? “An example of inferential statistics will be all patients 65 years and above with CHF will not experience hospital readmission if they receive follow-up telephone calls and visit by home health nurse 3 to 7 days post discharge.
References
Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th ed.). Sudbury, MA: Jones & Bartlett.
http://www.businessdictionary.com/definition/variable.htmlLinks to an external site.
Sample Answer 2 for NR 439 Week 6: Data Results and Analysis
Descriptive analysis serves a purpose to describe and understand the characteristics of the sample. According to the lesson, “Descriptive analysis of data is helpful in determining the characteristics of subjects and variables” (Houser, 2018). Examples of descriptive analysis is using a mean, median, and mode when determining the average grade of an assignment for a class, as chamberlain uses. Another example would be using range, standard deviation and variance when determining the variability of data. Inferential analysis is also known as quantitative analysis. This weeks lesson describes this type of analysis is “based on the assumption that chance or sampling error/random errors is the only explanation; however, researchers want to establish that chance/error is not the reason” (Nieswiadomy & Bailey, 2018, p. 250). This means that inferential analysis determines the strength and applicability of the findings and is an organized method using a mathematical and systematic approach. Qualitative analysis is also referred to as the results. According to the lesson, the nursing profession favors this type of analysis as it provides insight towards the patient preference and clinical experiences. When conducting my own research on qualitative analysis, I found that “Qualitative Data Analysis is outlined as the method of consistently looking and composing the interview records, observation notes, or completely different non-textual materials that the investigator accumulates to increase the understanding of an event.” (2021). I also learned that there are 5 different types of qualitative analysis. They consist of content analysis, narrative analysis, discourse analysis, framework analysis, and grounded theory. I found qualitative analysis the most interesting because there were so many subcategories to this 1 type of analysis.
I believe data analysis is necessary for discovering credible findings for nursing because of how much of a High Reliability Organization we are with pharmaceutical, physiological, and medical research. it is necessary for valid and truthful research to be conducted for such high stakes. When people’s lives are at stake, we cannot simply just base our practice of off nonreliable evidence, or undetailed statistics. We all aim to do no harm to our patients, and data analysis in research provides us with the best evidence based care for the safety, health, and well being of our patients.
Content analysis is either descriptive or interpretative, or basically asking yourself what is the data and what was meant by the data. Narrative analysis are stories, or transcribe experiences. The goal is to explicate stories in numerous contexts and experiences. Discourse analysis was the hardest for me to understand because it serves as an umbrella term for numerous meanings. The research explains that discourse analysis is a “general term for variety of approaches to analyze written, vocal, or language use or any vital philosophical theory event” and works well for political studies (2021). Framework analysis has 5 different phases to it. These are, familiarization which is just reading the information, then identifying a thematic framework, then coding the data, creating charts, then mapping out and interpreting the data, looking for patterns, ideas, and explanations. Finally, grounded theory is the gathering and analysis of the data. Ideas are technically “grounded” in the data., which means that the analysis and theories that develop concur when you have collected the information (2021).
Clinical significance is comparable to statistical significance because the statistics are based off the clinical experience. In different terms, statistical significance means something is going to happen, but the clinical significance shows on how broad of a spectrum something will occur. I believe that clinical significance is more meaningful to me when considering application of findings to my nursing practice, because a statistic just solely mean that we know that something is probably going to occur and an effect is taking place, whereas clinical significance is a critical tool for decision makers when dealing with high stakes research such as healthcare research because it seeks to understand the size and scope of an effect. It dives deeper into the research which makes it more trustworthy and reliable than just statistical significance.
References-
Houser, J. (2018). Nursing research: Reading, using, & creating evidence (4th ed.). Jones and Bartlett.
Nieswiadomy, R., & Bailey, C. (2018). Foundations of nursing research (7th ed.). Pearson.
What is qualitative data Analysis: Types of qualitative analysis. (2021, March 02). Retrieved April 07, 2021, from https://www.educba.com/what-is-qualitative-data-analysis/Links to an external site.
Sample Answer 3 for NR 439 Week 6: Data Results and Analysis
Question 1. Share what you learned about descriptive 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 in nursing.
Descriptive data: Numbers in a data set that are collected to represent research variables. Houser (2018). Descriptive date uses simple mathematical /calculations. Most are straightforward and can be done using a calculator. These techniques provide essential information in a research study. Researchers who created descriptive reports must have the correct statistical technique for the data that has been collected. The data must be presented so readers easily comprehend and don’t misunderstand. This also applies to nurses using statistical data in the clinical setting.
Inferential data: Statistical test to determine if results found in a sample are representative of a larger population. Houser (2018). It’s the differences that occurs between samples and populations, between groups or over time, because of changes. These changes are seen as risk factors in control studies. An event interference is used to determine if the outcome was affected by the change. It’s a generalization about a population which is based on sampling.
Qualitative analysis: Focuses on an understanding of the means end of an experience. From the individual perspective. Houser (2018). It focuses on verbal descriptions and the observation of behaviors to analyze for the conclusions. These methods are most appropriate for obtaining the meaning of the patient’s experience. Thus understanding what is the best therapeutic intervention. What I found interesting was these methods can work together best for me in the clinical setting. The researcher utilizes the clinical data collected that will best get the expected outcome.
Question 2. Compare Clinical significance and statistical significance, include which one is more meaningful to you when considering application of findings in nursing practice.
Clinical involves collecting data which involves people looking at understanding the disease, studying pattern, cause and how the disease effects the specific groups.
Statistical significance: Is a mathematical tool which determines whether the outcome of an experiment is the result of a relationship between specific factors or the result of chance. It claims that results from data by testing or experimentation does not occur randomly but is likely to be from a specific cause.
Clinical significance is more important to me. I can obtain the effectiveness of an intervention from the patient. This supports my nursing practice and validates the interventions chosen for the specific problems.
Reference,
Houser, J. (2018). Nursing research: Reading, using, and creating evidence (4th edition). Jones & Bartlett