HLT 362 Summary and Descriptive Statistics
Grand Canyon University HLT 362 Summary and Descriptive Statistics – Step-By-Step Guide
This guide will demonstrate how to complete the Grand Canyon University HLT 362 Summary and Descriptive Statistics 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 HLT 362 Summary and Descriptive Statistics
Whether one passes or fails an academic assignment such as the Grand Canyon University HLT 362 Summary and Descriptive Statistics 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 HLT 362 Summary and Descriptive Statistics
The introduction for the Grand Canyon University HLT 362 Summary and Descriptive Statistics 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 HLT 362 Summary and Descriptive Statistics
After the introduction, move into the main part of the HLT 362 Summary and Descriptive Statistics 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 HLT 362 Summary and Descriptive Statistics
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 HLT 362 Summary and Descriptive Statistics
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 HLT 362 Summary and Descriptive Statistics
Analysis of The Descriptive Statistics
Descriptive statistics is important in revealing special data trends in a population (Mishra et al.,2019). It can be used to explore disease trends such as diabetes (Abe et al.,2021), cancer, and other conditions among populations. The analyzed data was obtained from the National Cancer Institute, lung and bronchus cancer (“National Cancer”, n.d). The data has been expressed in terms of rates per one hundred thousand. The ethnic races considered in the data include whites (includes Hispanic), Hispanic (any race), black (includes Hispanic), Asian/Pacific Islander (includes Hispanic), and American Indian/Alaska Native (Includes Hispanic). The analyzed data covered the years 2000 to 2015.
The mean data covering the sixteen years shows that the blacks had the highest rates of cancer at 70.06 while the Hispanics had the lowest rates at 31.493. Median rates for the groups included 43.85, 38.9, 71.4, 32.1 and 64.55. It is also important to explore mode as part of descriptive statistics. Only three racial groups had mode, including Asian/Pacific Islanders, Hispanics, and whites. The observed modes were 36.6, 34.1, and 65.8 respectively. Variance was also calculated, with the blacks having the largest variance of 45.42 while the Asian/Pacific Islanders had the least variance at 5.679. The black race also recorded the highest range at 21.6, followed by the American Indian/Alaska Native at 19.7. The least variance was observed in Hispanics, where a value of 9 was observed. It is observable that the black has high rates, hence there is a need to use various approaches to reduce cancer rates. One of the recommended approaches is the use of culture-tailored education (Zhou et al.,2019). Another approach is early screening (Shah et al.,2019)
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References
Abe, T., Egbuche, O., Igwe, J., Jegede, O., Wagle, B., Olanipekun, T., & Onwuanyi, A. (2021). Cardiovascular complications in COVID‐19 patients with or without diabetes mellitus. Endocrinology, Diabetes & Metabolism, 4(2), e00218. Doi: 10.1002/edm2.218
Mishra, P., Pandey, C. M., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67. https://doi.org/10.4103%2Faca.ACA_157_18
National Cancer Institute. (n.d).Cancer stat facts: Lung and bronchus cancer. https://seer.cancer.gov/statfacts/html/lungb.html
Shah, S. C., Kayamba, V., Peek Jr, R. M., & Heimburger, D. (2019). Cancer control in low-and middle-income countries: is it time to consider screening?. Journal of Global Oncology, 5, 1-8. Doi: 10.1200/JGO.18.00200
Zhou, H., Zhang, Y., Liu, J., Yang, Y., Fang, W., Hong, S., … & Zhang, L. (2019). Education and lung cancer: a Mendelian randomization study. International Journal of Epidemiology, 48(3), 743-750. https://doi.org/10.1093/ije/dyz121
American Indian / Alaska Native (includes Hispanic) Asian / Pacific Islander (includes Hispanic) Black (includes Hispanic) Hispanic (any race) White (includes Hispanic) National Cancer Institute (2018) Lung and bronchus cancer. Retrieved from Janary 8, 2019 from https://seer.cancer.gov/explorer/application.php?site=47&data_type=1&graph_type=2&compareBy=race&chk_sex_1=1&chk_race_5=5&chk_race_4=4&chk_race_3=3&chk_race_6=6&chk_race_2=2&chk_age_range_1=1&chk_data_type_1=1&advopt_precision=1&advopt_display=1&showDataFor=sex_1_and_age_range_1_and_data_type_1 Year of Diagnosis Rate per 100,000 Rate per 100,000 Rate per 100,000 Rate per 100,000 Rate per 100,000
2000 45.7 41.8 77.8 34.2 68.8
2001 47.9 41 79 34.1 68.7
2002 44.6 40.4 75.8 34.1 68
2003 50 40.9 77.3 34.5 67.1
2004 51.7 40.5 75.1 35 65.8
2005 48.7 40.2 73.7 33.8 65.9
2006 46.4 39.8 73.4 32 65.8
2007 43.1 38.8 71.2 32.7 65.2
2008 45 38.5 70.8 32.2 63.9
2009 40.1 39 71.6 31.8 63.1
2010 42.4 37 67.8 30.3 60.4
2011 39.6 36.6 64.1 29.4 58.5
2012 36.6 36.7 64.3 28.2 57.5
2013 39.9 36.6 60.5 28.8 56.3
2014 32 34 61.3 26.8 55.4
2015 38.7 34.4 57.4 26 53.2
Mean 43.275 38.5125 70.06875 31.49375 62.725
Median 43.85 38.9 71.4 32.1 64.55
Mode #N/A 36.6 #N/A 34.1 65.8
variance 27.71933333 5.679833333 45.42895833 8.399291667 26.162
Standard deviation 5.097732339 2.307562296 6.526074504 2.806124719 4.952461509
Range 19.7 7.8 21.6 9 15.6
Sample Answer 2 for HLT 362 Summary and Descriptive Statistics
Summary and Descriptive Statistics
Descriptive statistics plays a critical role in data analysis and interpretation as it allows the researchers to have an insight into population trends. For instance, it can be used to study various data trends existing in conditions such as obesity, diabetes, and other chronic illnesses. Data analysis was performed for data obtained from the National Cancer Institute, lung and bronchus cancer (“National Cancer,” n.d). This data expressed various aspects of cancer prevalence in different populations. Various ethnic races have been represented in the data, including Whites (includes Hispanic), Hispanic (any race), black (includes Hispanic), Asian/Pacific Islander (includes Hispanic), and American Indian/Alaska Native (Includes Hispanic).
The data covered a period of 16 years (from 2000 to 2015). During that time duration, the Hispanics recorded the lowest rates ( a mean of 31.493). On the other hand, the highest mean was observed among the blacks at a mean of 70.06. The observed median rates during this time frame were 64.55, 32.1, 71.4, 38.9 and 43.85. Mode values were only observed in three ethnic groups, including whites, Hispanics, and Asian/Pacific Islanders; values of 65.8, 34.1, and 36.6 were observed. The black ethnic group recorded the biggest variance of 45.42. On the other hand, the Asian/Pacific Islanders recorded the least variance (5.679). While the lowest range of 9 was observed in Hispanics, the black race recorded the largest value of 21.6. The trends in the data revealed that the black race had higher rates of cancer, which implies the need to use appropriate strategies to reduce such rates.
References
National Cancer Institute. (n.d). Cancer stat facts: Lung and bronchus cancer. https://seer.cancer.gov/statfacts/html/lungb.html
HLT 362 Topic 5 Article Analysis and Evaluation of Research Ethics Sample Answer
Article Analysis and Evaluation of Research Ethics
Article Citation and Permalink (APA format) | Article 1 Wong, H., Karaca, Z., & Gibson, T. B. (2018). A Quantitative Observational Study of Physician Influence on Hospital Costs. INQUIRY: The Journal of Health Care Organization, Provision, and Financing, 55, 0046958018800906. Permalink: 10.1177/0046958018800906
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Point | Description |
Broad Topic Area/Title | The main topic in the above article is the impacts of physicians on the hospital costs. The article takes the quantitative approaches to compare different variables involved in the study. |
Problem Statement (What is the problem research is addressing?) | The problem that the research is addressing in the variation in healthcare costs that is causing some patients to pay more for the medical services. Over the years, it has been established that the costs of healthcare services vary significantly according to the geography. Many investigators have attempted to question the above variation whether it is due to the patient health status, practice patterns, prices, patient characteristics, as well as the individual provider decision-making processes. |
Purpose Statement (What is the purpose of the study?) | The purpose of the study is to show the impacts of physicians on the hospital costs. The incorporates their activities as well as the processes that they often undertake to reduce prices in the healthcare system. |
Research Questions (What questions does the research seek to answer?) |
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Define Hypothesis (Or state the correct hypothesis based upon variables used) | Null Hypothesis: There is no strong relationship between the costs of hospital services and the physician characteristics such as gender, age and the level of training. Alternative Hypothesis: There is no strong relationship between the costs of hospital
services and the physician characteristics such as gender, age and the level of training. Null Hypothesis: There is negative association between the physician’s years of experience and the average costs of hospital inpatient stay. Alternative Hypothesis: There is a positive association between the physician’s years of experience and the average costs of hospital inpatient stay Null Hypothesis: Physicians have no impacts in the hospital costs and the general costs in healthcare Alternative Hypothesis: Physicians have impacts in the hospital costs and the general costs in healthcare |
Identify Dependent and Independent Variables and Type of Data for the Variables | Dependent variables
Independent variable
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Population of Interest for Study | The population of interest for the study were the physicians across the selected two states of the United States of America, Arizona and Florida. |
Sample | The sample size for the study was 15, 237 physicians. |
Sampling Method | Simple random sampling |
Identify Data Collection Identify how data were collected | The data applied in the study were obtained from the hospital databases and the Florida Department of Health as well as the Arizona Board of Medical Examiners. |
Summarize Data Collection Approach | The processes of acquiring data involved seeking permission from the data partners, presentation of licenses to gain access to the data. Researchers did not enter directly to the databases, they specified the kinds of data they needed and samples were retrieved by the data managers after permission from the authorities were granted. |
Discuss Data Analysis Include what types of statistical tests were used for the variables. | In the process of analysis, the authors utilized descriptive statistics to show the attributes of data including the percentage of gender involved in the study, types of training for each physician, age, and the nature of work that they do. To test the hypothesis, the researcher employed sensitivity analysis where several scenarios were employed to test the robustness of the results. The propensity score nearest tests were also used to develop subsamples. Finally, there was regression analysis to show the relationship between variables and the average costs for hospital visits. |
Summarize Results of Study | From the study, there was a significant disparity in the cost of producing medical services and the physician characteristics including age, gender, and the level of education (Wong, Karaca, & Gibson, 2018). There was negative association between the physician’s years of experience and the average costs of healthcare services. Lastly, there was a sizable variation in the average costs of healthcare across different hospitals. The costs were associated with the expertise, age and the level of experience among the physicians (Wong, Karaca, & Gibson, 2018). |
Summary of Assumptions and Limitations Identify the assumptions and limitations from the article. Report other potential assumptions and limitations of your review not listed by the author. | From the article, one of the main assumption was that the data obtained from the two state’s databases were continuous. There was also an assumption of the equality of variance. In other words, when testing for the hypothesis, the dataset used were assumed to exhibit equal variances. Dataset with the continuous data were also assumed to be normally distributed. The limitation of the research is that there was the use of secondary data which were not gathered by the researcher. It was therefore very difficult to formulate the variables and the required statistical hypothesis. The study also lacked statistical support from other studies previously conducted on the same topic.
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Ethical Considerations
From the article, there were several ethical considerations that dictated the processes of data collection and analysis. First, there was the consent and seeking of information from the relevant authorities during the acquisition of datasets from the state’s databases. Usually, before engaging in the use of data, it is necessary to seek for information from the relevant authorities. On the other hand, handling of data is critical in data analysis processes (Žukauskas, Vveinhardt & Andriukaitienė, 2018). From the article, the authors ensured the privacy of information. Some of the databases assessed contained physician’s information as well as the hospital’s data on financial issues. These data were supposed to be kept secret (Resnik, 2018). While analyzing the data, the standardized methods were used to ensure the accuracy of the outcome and to report appropriate results in line with the healthcare institutions. In other words, ethical practices of reporting were employed to ensure that the information were accurate. While conducting the research, there was avoidance of deceptive practices accuracy was withheld at all cost, from the time of acquisition of data to the time of reporting of results. The databases used were also accurate and well maintained and secured. While accessing these databases, there was the consideration of high level of expertise to ensure that the datasets obtained were authentic. The findings underwent a lot of verifications before the publication processes. In other words, there was the involvement of different stakeholders to ensure that the data obtained and the processes of analysis were accurate and in line with the data obtained from the state’s databases. The evaluation process follows an ideal procedure setup by the Grand Canyon University. In other words, it accurately adheres to the laid down procedures of the research and article analysis.
References
Resnik, D. B. (2018). The ethics of research with human subjects: Protecting people, advancing science, promoting trust.
Wong, H., Karaca, Z., & Gibson, T. B. (2018). A Quantitative Observational Study of Physician Influence on Hospital Costs. INQUIRY: The Journal of Health Care Organization, Provision, and Financing, 55, 0046958018800906.
Žukauskas, P., Vveinhardt, J., & Andriukaitienė, R. (April 18, 2018). Corrections of Research Instrument.