# Search the GCU Library and find three different health care articles that use quantitative research. Do not use articles that appear in the topic Resources or textbook

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The interpretation of research in health care is essential to decision making. By understanding research, health care providers can identify risk factors, trends, outcomes for treatment, health care costs and best practices. To be effective in evaluating and interpreting research, the reader must first understand how to interpret the findings.

**For this assignment:**

Search the GCU Library and find three different health care articles that use quantitative research. Do not use articles that appear in the topic Resources or textbook. Complete an article analysis for each using the “Article Analysis 1” template.

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Order Paper NowRefer to the “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial,” in conjunction with the “Article Analysis Example 1,” for an example of an article analysis.

While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

**Article Analysis 1 – Rubric**

1, Three articles are presented. All three articles are based on quantitative research

2, Article citation and permalink are presented. Article citation is accurately presented in APA format. Page numbers are accurate and used in all areas when citing information.

3, Broad topic area and title are fully presented and accurate.

4, Variable types and data for variables are presented and accurate.

5, Population of interest for the study is presented and accurate

6, Sample is presented and accurate

7, Sampling method is presented and accurate.

8, Descriptive Statistics (mean, median, mode; standard deviation) (Identify examples of descriptive statistics in the article.)

9, Inferential statistic examples from the article are presented and accurate.

10, The writer is clearly in command of standard, written, academic English

Statistics have been utilized in healthcare since at least the 19th century. Florence Nightingale used a statistical approach to decrease the mortality rate of British troops in Crimea. Her meticulous records were a key to present-day statistical quality measurement, and she was an innovator in the collection, tabulation, interpretation, and graphical display of descriptive statistics. She named her visual data display a “Coxcomb,” known today as a pie- chart (Sheingold & Hahn, 2014). Clara Barton applied the same analysis in the United States during the Civil War.

Louis Pasteur applied statistics in his research of microbes and the “germ theory” to create penicillin. This evidence led to the wide-scale adoption of antiseptic practices by physicians and hospitals throughout Europe and eventually in the U.S. Pasteur’s research also led to the development of “pasteurization,” which utilizes heat to destroy harmful microbes in perishable food while leaving the food undamaged (Sheingold & Hahn, 2014).

Dr. Rupert Blue was responsible for providing leadership in America during the worst disease outbreak in U.S. history. The Influenza Pandemic of 1918 killed fifty (50) million or 1/5 of the world’s population, representing more people than died during World War I. During the Influenza Pandemic, Dr. Blue’s quality tools were quarantine, mandatory medical exams for all immigrants entering the country, communication in the form of weekly newsletters that contained information about the latest outbreaks, and the results of influenza research conducted at the Hygienic Laboratory which continues to exist today (Sheingold & Hahn, 2014).

The medical records during the 1918 influenza pandemic inform how we should respond to a similar widespread outbreak of biological disease and provide data on the long-term effects of the flu on a pregnant woman.

Reference:

Sheingold, B. H., Hahn, J. A. (2014). The history of healthcare quality: The first 100 years 1860- 1960. International Journal of Africa Nursing Sciences. Vol. 1. Pages 18 – 22. DOI: https://doi.org/10.1016/j.ijans.2014.05.002

**Unread**

In 1992, Anderson and May published Infectious Disease of Humans, documenting their work in mathematical modeling transmission of infectious diseases, which was critically important to understanding the ongoing work in fighting the global HIV epidemic, as well as malaria and tuberculosis. Subsequent work on modeling diseases has been used to monitor and model the impact of influenza outbreaks. During the 1990s, laboratory techniques improved enough so that strains of viruses could be mapped and links made to the epidemiologic investigation.

Reference:

Anderson RM, May RM. Infectious diseases of humans: dynamics and control. New York, NY: Oxford University Press; 1992.

Hello professor and class,

Statistics is a significant element in healthcare today. Various medical assessments rely heavily on statistics to gather crucial data for enhancing care provision. For instance, statistical measurements like temperature, body mass index, and respiratory rates are used to diagnose various illnesses. Moreover, statistical analyses are carried out on data in electronic health records to identify health issues and plan to address them (Sharples, 2018). Statistical application of healthcare began with the creation of the Royal Statistical Society in 1834, with one of the pioneers of nursing, Florence Nightingale, being a member (CDC, 2011). The health body carried out statistical analysis to understand the epidemiology of diseases and enhance the field of public health. Florence Nightingale and the Royal Statistical Society contributed to the utilization of statistical evidence in healthcare. Statistical evidence was used to identify the reasons for significant death rates and to make informed decisions to improve healthcare provision.

Besides Florence Nightingale, who contributed significantly to the application of statistics in healthcare, other people have contributed to its advancement and utilization. According to CDC (2011), Alexandar Langmuir, a leader of the Center for Disease Control in 1961, emphasized the collection of data and applying the data in healthcare through public health surveillance. Another significant statistical contribution was made by Carl Norden. According to CDC (2011), Carl Norden was the first healthcare professional to implement the t-test in research when carrying out an epidemic-assistance investigation. In the modern-day, health researchers have significantly utilized the t-test in hypothesis testing when carrying out research. James Bryan also contributed to the use of the pie chart in representing data during research. He carried out an epidemic-assistance investigation that utilized data collection through public surveillance, as emphasized by Alexander Langmuir, and utilized the pie chart to portray the data. These contributions have significantly changed healthcare since they have advanced research to enhance the investigation of various health concerns and develop solutions.

**References**

CDC. (2011). *History of statistics in public health at CDC, 1960-2010: The rise of statistical evidence.* History of Statistics in Public Health at CDC, 1960–2010: the Rise of Statistical Evidence

Sharples, L. D. (2018). The role of statistics in the era of big data: Electronic health records for healthcare research. *Statistics & Probability Letters*, *136*, 105-110.

**Unread**

Hello Yvette,

I really enjoyed reading your discussion post and found it very educative! I for one found finding just one person who changed healthcare, but you went above and beyond to find many more. Statistics play a key role in healthcafre especially when finding new ways to better the clinic and to make new decisions. As you have shown, statistics have been proven to be effective when used properly and are responsible for aiding in countless great accomplishments within healthcare. Overall great post!

**HLT 362V Topic 1 Discussion 1**

Discuss the historical application of statistics in the field of health care. Describe an example, other than Florence Nightingale’s contributions, where statistical application has greatly influenced or changed health care operations or practice.

**HLT362V Topic 1 Discussion 2**

Discuss why it is important for a person working in health care to understand statistical concepts. Provide an example of how statistical data is used in your organization or specialty area today and what you are expected to do with this information as a practitioner.

Hello Yvette,

I really enjoyed reading your discussion post and found it very educative! I for one found finding just one person who changed healthcare, but you went above and beyond to find many more. Statistics play a key role in healthcafre especially when finding new ways to better the clinic and to make new decisions. As you have shown, statistics have been proven to be effective when used properly and are responsible for aiding in countless great accomplishments within healthcare. Overall great post!

**HLT 362V Topic 1 Discussion 1**

Discuss the historical application of statistics in the field of health care. Describe an example, other than Florence Nightingale’s contributions, where statistical application has greatly influenced or changed health care operations or practice.

**HLT362V Topic 1 Discussion 2**

Discuss why it is important for a person working in health care to understand statistical concepts. Provide an example of how statistical data is used in your organization or specialty area today and what you are expected to do with this information as a practitioner.

**HLT 362V**

## HLT 362V – Global Healthcare DQ1

HLT 362V – Global Healthcare DQ1

Identify two areas of nursing practice, which evidence-based practice has improved patient outcomes. State the study and its impact on patient care. How have these findings changed your nursing practice? Please support your response with a minimum of two supporting peer reviewed articles.

### Sample Response for HLT 362V – Global Healthcare DQ1

Re:Topic 1 DQ 1

Patient safety is a global healthcare concern. Registered nurses as direct providers of care have an integral role in keeping patients safe. Medication error, including medication administration error, is the most frequent cause of preventable morbidity and mortality in hospitals. According to the American Nurse Association (2010), an error can happen at any step. Although many errors arise at the prescribing stage, some are intercepted by pharmacists, nurses, or other staff. Some of the causes for medication errors include storage of look-alike medications and labelling. Heavier workloads also are associated with medication errors. HLT 362V – Global Healthcare DQ1.

According to Briggs (2010) there is evidence that suggests that having two nurses check medication orders prior to dispensing medication significantly reduces the incidence of medication errors. Additionally, computer based system whereby the physician writes all orders online is very effective in reducing medication errors in a general hospital population. One study found that in 44% of cases where the system alerted the physician to a potential risk of an adverse drug event related injury, the physician was unaware of the risk.

Another strategy for reducing medication errors is to establish adequate quality processes and risk-management strategies. HLT 362V – Global Healthcare DQ1. Every facility should have a culture of safety that encourages discussion of medication errors and near-misses (errors that don’t reach a patient) in a non-punitive fashion (ANA, 2010).

Another area of safety is hand hygiene. Evidence to support the importance of hand hygiene in preventing infection dates back to the 1800s (World Health Organization [WHO], 2009).

**HLT 362V Week 1 Assignment: Mean, Variance and Standard Deviation Worksheet**

**HLT362V Week 1 Workbook Exercise 6, 8, 9, 11, 16, 27**

**HLT 362V Week 2 Assignment, Population and Sampling Distribution Worksheet**

**HLT362V Week 2 Workbook Exercise 10, 18, 26**

**HLT 362V Week 3 Benchmark Assignment, Hypothesis Testing Worksheet**

**HLT 362V Week 3 Workbook Exercise 16, 17, 20, 31, 32**

**HLT362V Week 4 Assignment, ANOVA Excel Worksheet. HLT 362V – Global Healthcare DQ1**

**HLT 362V Week 4 Workbook Exercise 18, 33, 36**

**HLT 362V Week 5 Assignment, Correlation-Regression and Chi Square Worksheet**

**HLT362V Week 5 Workbook Exercise 14, 19, 23, 24, 29, 35**

### HLT 362 Applied Statistics for Health care Professionals

**Week 1 Discussion**

DQ1 Discuss the historical application of statistics in the field of health care. Describe an example, other than Florence Nightingale’s contributions, where statistical application has greatly influenced or changed health care operations or practice.

DQ2 Discuss why it is important for a person working in health care to understand statistical concepts. Provide an example of how statistical data is used in your organization or specialty area today and what you are expected to do with this information as a practitioner.

**Week 2 Discussion**

DQ1 Select a research article, other than the articles from your assignments, from the library. Provide an overview of the study and describe the strategy that was used to select the sample from the population. Evaluate the effectiveness of the sampling method selected. Provide support for your answer. Include the article title and permalink in your post.

DQ2 Using the research article selected for DQ 1, identify three key questions you will ask and answer when reading the research study and why these questions are important. When responding to peers, provide other questions and answers that could be considered in relation to the peers’ studies.

**Week 3 Discussion**

DQ1 Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions.

DQ2 Evaluate and provide examples of how hypothesis testing and confidence intervals are used together in health care research. Provide a workplace example that illustrates your ideas.

**Week 4 Discussion**

DQ1 Provide an example of experimental, quasi-experimental, and nonexperimental research from the Library and explain how each research type differs from the others. When replying to peers, evaluate the effectiveness of the research design of the study for two of the examples provided.

DQ2 Describe the difference between research and quality improvement. Provide a workplace example where qualitative and quantitative research is applied and how it was used within your organization. When replying to peers, discuss how these research findings might be incorporated into another health care setting.

**Week 5 Discussion**

DQ1 Describe how epidemiological data influences changes in health practices. Provide an example and explain what data would be necessary to make a change in practice.

DQ2 Discuss ways your organization uses technology to gather patient and health care information, and how this information and data are used to direct patient care and outcomes.

**Week 1 Assignment**

Application of Statistics in Health Care

Statistical application and the interpretation of data is important in health care. Review the statistical concepts covered in this topic. In a 750-1,000 word paper, discuss the significance of statistical application in health care. Include the following:

Describe the application of statistics in health care. Specifically discuss its significance to quality, safety, health promotion, and leadership.

Consider your organization or specialty area and how you utilize statistical knowledge. Discuss how you obtain statistical data, how statistical knowledge is used in day-to-day operations and how you apply it or use it in decision making.

Three peer-reviewed, scholarly or professional references are required.

Prepare this assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

**Week 2 Assignment**

Article Analysis 1

The interpretation of research in health care is essential to decision making. By understanding research, health care providers can identify risk factors, trends, outcomes for treatment, health care costs and best practices. To be effective in evaluating and interpreting research, the reader must first understand how to interpret the findings. You will practice article analysis in Topics 2, 3, and 5.

For this assignment:

Search the Library and find three different health care articles that use quantitative research. Do not use articles that appear in the Topic Materials or textbook. Complete an article analysis for each using the “Article Analysis 1” template.

Refer to the “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial,” in conjunction with the “Article Analysis Example 1,” for an example of an article analysis.

While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance

**Article Analysis 1**

Article Citation and Permalink(APA format)

Article 1

Article 2

Article 3

Point

Description

Description

Description

Broad Topic Area/Title

Identify Independent and Dependent Variablesand Type of Data for the Variables

Population of Interest for the Study

Sample

Sampling Method

Descriptive Statistics (Mean, Median, Mode; Standard Deviation)

Identify examples of descriptive statistics in the article.

Inferential Statistics

Identify examples of inferential statistics in the article.

**Week 3 Assignment**

Article Analysis 2

Search the Library and find two new health care articles that use quantitative research. Do not use articles from a previous assignment, or articles that appear in the Topic Materials or textbook.

Complete an article analysis for each using the “Article Analysis: Part 2” template.

Refer to the “Patient Preference and Satisfaction in Hospital-at-Home and Usual Hospital Care for COPD Exacerbations: Results of a Randomised Controlled Trial,” in conjunction with the “Article Analysis Example 2,” for an example of an article analysis.

While APA style is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

**Week 4 Assignment**

Quality Improvement Proposal

Identify a quality improvement opportunity in your organization or practice. In a 1,250-1,500 word paper, describe the problem or issue and propose a quality improvement initiative based on evidence-based practice. Apply “The Road to Evidence-Based Practice” process, illustrated in Chapter 4 of your textbook, to create your proposal.

Include the following:

Provide an overview the problem and the setting in which the problem or issue occurs.

Explain why a quality improvement initiative is needed in this area and the expected outcome.

Discuss how the results of previous research demonstrate support for the quality improvement initiative and its projected outcomes. Include a minimum of three peer-reviewed sources published within the last 5 years, not included in the course materials or textbook, that establish evidence in support of the quality improvement proposed.

Discuss steps necessary to implement the quality improvement initiative. Provide evidence and rationale to support your answer.

Explain how the quality improvement initiative will be evaluated to determine whether there was improvement.

Support your explanation by identifying the variables, hypothesis test, and statistical test that you would need to prove that the quality improvement initiative succeeded.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance.

**Week 5 Assignment**

Summary and Descriptive Statistics

There is often the requirement to evaluate descriptive statistics for data within the organization or for health care information. Every year the National Cancer Institute collects and publishes data based on patient demographics. Understanding differences between the groups based upon the collected data often informs health care professionals towards research, treatment options, or patient education.

Using the data on the “National Cancer Institute Data” Excel spreadsheet, calculate the descriptive statistics indicated below for each of the Race/Ethnicity groups. Refer to your textbook and the Topic Materials, as needed, for assistance in with creating Excel formulas.

Provide the following descriptive statistics:

Measures of Central Tendency: Mean, Median, and Mode

Measures of Variation: Variance, Standard Deviation, and Range (a formula is not needed for Range).

Once the data is calculated, provide a 150-250 word analysis of the descriptive statistics on the spreadsheet. This should include differences and health outcomes between groups.

APA style is not required, but solid academic writing?is expected.

You are not required to submit this assignment to LopesWrite.

**Week 5 Assignment**

Article Analysis and Evaluation of Research Ethics

Search the Library and find one new health care article that uses quantitative research. Do not use an article from a previous assignment, or that appears in the Topic Materials or textbook.

Complete an article analysis and ethics evaluation of the research using the “Article Analysis and Evaluation of Research Ethics” template. See Chapter 5 of your textbook as needed, for assistance.

You are required to submit this assignment to LopesWrite. Refer to the LopesWrite Technical Support articles for assistance

Article Analysis and Evaluation of Research Ethics

Article Citation and Permalink

**Ethical Considerations**

Evaluate the article and identify potential ethical considerations that may have occurred when sampling, collecting data, analyzing data, or publishing results. Summarize your findings below in 250-500 words. Provide rationale and support for your evaluation.

**PUB-550: Application and Interpretation of Public Health Data**

### Topic 1: Data Management and Descriptive Statistics

- Evaluate methods of data organization.
- Compare characteristics of correlational, experimental, and quasi-experimental (observational) statistics variables.
- Identify the four levels of measurement.
- Differentiate between a population and a sample, and a parameter and a statistic (descriptive and inferential).
- Explain the role of quantitative and qualitative methods and sciences in describing and assessing a population’s health. PUB-550: Application and Interpretation of Public Health Data
- Evaluate public health data sources.
- Apply methods to calculate and communicate descriptive statistics.

Select a research article, other than the articles from your assignments, from the GCU library. Provide an overview of the study and describe the strategy that was used to select the sample from the population. Evaluate the effectiveness of the sampling method selected. Provide support for your answer. Include the article title and permalink in your post.

**HLT362V Topic 2 Discussion 2**

Using the research article selected for DQ 1, identify three key questions you will ask and answer when reading the research study and why these questions are important. When responding to peers, provide other questions and answers that could be considered in relation to the peers’ studies.

**HLT362V**

Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions.

**HLT362V Topic 3 Discussion 2**

Evaluate and provide examples of how hypothesis testing and confidence intervals are use together in health care research. Provide a workplace example that illustrates your ideas.

**HLT362V **

Provide an example of experimental, quasi-experimental, and nonexperimental research from the GCU Library and explain how each research type differs from the others. When replying to peers, evaluate the effectiveness of the research design of the study for two of the examples provided.

**HLT362V Topic 4 Discussion 2**

Describe the difference between research and quality improvement. Provide a workplace example where qualitative and quantitative research is …..and how it was use within your organization. When replying to peers, discuss how these research findings might be incorporated into another health care setting.

**HLT362V TOPIC 5 DISCUSSION 1**

Describe how epidemiological data influences changes in health practices. Provide an example and explain what data would be necessary to make a change in practice.

**HLT362V Topic 5 Discussion 2**

Discuss ways your organization uses technology to gather patient and health care information, and how this information and data are use to direct patient care and outcomes.

##### Exercise 14

**Understanding Simple Linear Regression**

- According to the study narrative and Figure 1 in the Flannigan et al. (2014) study, does the APLS UK formulae under- or overestimate the weight of children younger than 1 year of age? Provide a rationale for your answer.
- Using the values a = 3.161 and b = 0.502 with the novel formula in Figure 1, what is the … weight in kilograms (kg) for a child at 9 months of age? Show your calculations.
- Using the values a = 3.161 and b = 0.502 with the novel formula in Figure 1, what is the … weight in kilograms for a child at 2 months of age? Show your calculations.
- In Figure 2, the formula for calculating y (weight in kg) is Weight in kg = (0.176 × age in months) + 7.241. Identify the y intercept and the slope in this formula.
- Using the values a = 7.241 and b = 0.176 with the novel formula in Figure 2, what is the … weight in kilograms for a child 3 years of age? Show your calculations.
- Using the values a = 7.241 and b = 0.176 with the novel formula in Figure 2, what is the … weight in kilograms for a child 5 years of age? Show your calculations.
- In Figure 3, some of the actual mean weights represented by the blue line with squares are above the dotted straight line for the novel formula, but others are below the straight line. Is this an expected finding? Provide a rationale for your answer.
- In Figure 3, the novel formula is (Weight in kilograms = (0.331 × Age in months) – 6.868. What is the predicted weight in kilograms for a child 10 years old? Show your calculations.
- Was the sample size of this study adequate for conducting simple linear regression? Provide a rationale for your answer.
- Describe one potential clinical advantage and one potential clinical problem with using the three novel formulas presented in Figures 1, 2, and 3 in a PICU setting.

##### Exercise 19

**Understanding Pearson Chi-Square**

- According to the relevant study results section of the Darling-Fisher et al. (2014) study, what categories are reported to be statistically significant?
- What level of measurement is appropriate for calculating the χ2 statistic? Give two exam¬ples from Table 2 of demographic variables measured at the level appropriate for χ2.
- What is the χ2 for U.S. practice region? Is the χ2 value statistically significant? Provide a rationale for your answer. X2= 29.68; p= <.00
- What is the df for provider type? Provide a rationale for why the df for provider type pre¬sented in Table 2 is correct.
- Is there a statistically significant difference for practice setting between the Rapid Assessment for Adolescent Preventive Services (RAAPS) users and nonusers? Provide a rationale for your answer.
- State the null hypothesis for provider age in years for RAAPS users and RAAPS nonusers.
- Should the null hypothesis for provider age in years developed for Question 6 be accepted or rejected? Provide a rationale for your answer.
- Describe at least one clinical advantage and one clinical challenge of using RAAPS as described by Darling-Fisher et al. (2014).
- How many null hypotheses are rejected in the Darling-Fisher et al. (2014) study for the results presented in Table 2? Provide a rationale for your answer.
- A statistically significant difference is present between RAAPS users and RAAPS nonusers for U.S. practice region, χ2 = 29.68. Does the χ2 result provide the location of the difference? Provide a rationale for your answer.

##### Exercise 29

**Calculating Simple Linear Regression**

- If you have access to SPSS, compute the Shapiro-Wilk test of normality for the variable age (as demonstrated in Exercise 26). If you do not have access to SPSS, plot the frequency distributions by hand. What do the results indicate?
- State the null hypothesis where age at enrollment is used to predict the time for comple¬tion of an RN to BSN program.
- What is b as computed by hand (or using SPSS)?
- What is a as computed by hand (or using SPSS)?
- Write the new regression equation.
- How would you characterize the magnitude of the obtained R2 value? Provide a rationale for your answer.
- How much variance in months to RN to BSN program completion is explained by knowing the student’s enrollment age?
- What was the correlation between the actual y values and the predicted y values using the new regression equation in the example?
- Write your interpretation of the results as you would in an APA-formatted journal.
- Given the results of your analyses, would you use the calculated regression equation to predict future students’ program completion time by using enrollment age as x? Provide a rationale for your answer.

**HLT 362V Module 1 Mean Variance Standard Deviation**

Please type you answer in the cell beside the question.

- Identify the sampling technique being used. Every 20th patient that comes into the emergency room is given a satisfaction survey upon their discharge.
- random sampling
- cluster sampling
- systematic sampling
- stratified sampling
- none of the above
- The formula for finding the sample mean is ______________.
- The formula for finding sample standard deviation is ________________.

** **

**HLT 362V Module 1 Exercise 16 Done**

1- The researchers analyzed the data they collected as though it were at what level of measurement? (Your choices are: Nominal, Ordinal, Interval/ratio, or Experimental)

2- What was the mean posttest empowerment score for the control group?

3- Compare the mean baseline and posttest depression scores of the experimental group. Was this an expected finding? Provide a rationale for your answer.

4- Compare the mean baseline and posttest depression scores of the control group. Do these scores strengthen or weaken the validity of the research results? Provide a rationale for your answer.

5- Which group’s test scores had the least amount of variability or dispersion? Provide a rationale for your answer.

6 – Did the empowerment variable or self-care self-efficacy variable demonstrate the greatest amount of dispersion? Provide a rationale for your answer.

7 – The mean (X ̅) is a measure of a distribution while the SD is a measure of its scores. Both X ̅ and SD are statistics.

8 – What was the mean severity for renal disease for the research subjects? What was the dispersion or variability of the renal disease severity scores? Did the severity scores vary significantly between the control and the experimental groups? Is this important? Provide a rationale for your answer.

9 – Which variable was least affected by the empowerment program? Provide a rationale for your answer.

10 – Was it important for the researchers to include the total means and SDs for the study variables in Table 2 to promote the readers’ understanding of the study results? Provide a rationale for your answer.

**HLT 362V M2 Population Sampling Distribution**

For a normal distribution that has a mean of 100 and a standard deviation of 8. Determine the Z-score for each of the following X values:

X = 108

X = 112

X = 98

X = 70

X = 124

Use the information in 1 A to determine the area or probability of the following:

P(x > 108)

P(x

HLT362 Week 3 Quiz.docx practice exam questions with answers 2021 solution

If you are conducting a study on the impacts of diet and exercise on high blood pressure and you take a

proportional sample based upon race/ethnicity, this would be an example of: ok

Simple random sample

Cluster sampling

Stratified sampling

Convenience sampling

• If a researcher does not select the appropriate level of significance (alpha) based upon prior

research or industry standard and concludes that the study found a statistical difference when in

fact there was no difference, this is referred to as: ok

Validity

Reliability

Type I error

Type II error

• To obtain a sample of 20 patients in ICU, clinician goes to the ICU and selects the current

patients. This is an example of a: ok

Judgement sampling

Simple random sampling

Snowball sampling

Data often appear disordered and it is difficult to see any connections or relationships. Ordering the data by certain variables or grouping variables into specific categories, such as age or sex categories, can help bring clarity to the data. Knowing how to organize data is an important skill to initiate the analytical process.

For this assignment, students will use Excel and SPSS Statistics to order variables. Using the “Example Dataset,” complete the steps below using both Excel and SPSS Statistics. View the Excel and SPSS tutorials for assistance in completing this assignment. Submit one Word document and include a screen shot of the data after completing the first two steps of Part 1 in Excel and SPSS to compare your results. Use a second Word document to complete Part 2 of the assignment. PUB-550: Application and Interpretation of Public Health Data

*Part 1: Ordering and Grouping Data Using Excel and SPSS*

For Part 1, accomplish the following:

- Order (sort) observations according to age.
- Group observations by sex and investigate the age and income for males and females.
- Create a new variable titled “Exercise Group” based on the variable “Minutes Exercise.” Use the following categories to create your groups: 1 = 0-30 minutes; 2 = 31-60 minutes; 3 = 61-90 minutes; 4 = 91-120 minutes; and 5 = 120+ minutes.

*Part 2: Data Interpretation*

Study the results of the dataset grouping and ordering. Discuss the following in a 500-750 word summary:

- Describe the measurement levels for each of the variables in the dataset.
- Discuss what you learned from ordering the data by age and why this information is important.
- Describe the process you used to group the data in Excel and SPSS.
- Describe what you learned by grouping the variables by category of exercise.
- Are these data from a correlational study, experimental study, or quasi-experimental (observational) study? Discuss your rationale and identify a study question appropriate for this dataset. PUB-550: Application and Interpretation of Public Health Data

*General Requirements*

Submit the Word document to the instructor.

APA style is not required, but solid academic writing is expected.

A local community organization was interested in learning about general health behaviors in the area and the relationships between health behaviors and environmental and social determinants. They decided to conduct a brief survey based on a convenient sample of people visiting the local shopping mall. They offered a $5 incentive for completing the survey. The Topic 1 Example dataset includes 30 observations from this survey. Use this data to complete the relevant assignments in this course. | |||||||||||||||

Education Level | |||||||||||||||

1 | Less than High School | ||||||||||||||

2 | Graduated High School | ||||||||||||||

3 | Graduated College | ||||||||||||||

Annual Income = US Dollars
Mixed methods research is becoming an important approach in generating public health evidence. Based on the resources supplied, discuss the benefits of a mixed methods approach. Include an explanation of the differences between qualitative and quantitative research and the purpose of each. Topic 1 DQ 1Mixed methods research has become increasing popular, however the definition of mixed methods research has yet to be agreed upon (Ozawa & Pongpirul, 2014). Essentially, mixed methods research studies incorporate quantitative and qualitative data to utilize the strengths of both types of research methods (Ozawa & Pongpirul, 2014). In health systems, mixed methods research is critical because it allows researchers to see issues from various perspectives, contextualize information, have a better understanding of the issue, form results, quantify difficult measures, create illustrations for trends, and examine processes (Ozawa & Pongpirul, 2014).To make sense of the assembly of mixed method research designs, there are four categories; the triangulation design, the embedded design, the explanatory design, and the exploratory design (Almalki, 2016). The triangulation design is practical because this type of research gathers data from different sources and utilizes different methods, which all work together as well-organized design (Almalki, 2016). With the embedded design, less resources are needed, and it produces less data, making it easier for researchers to grasp (Almalki, 2016). The explanatory design is easy to implement, and it enables the focus of the research to be maintained (Almalki, 2016). With the exploratory design, separate stages are easy to apply, also qualitative information is acceptable to quantitative researchers (Almalki, 2016).Quantitative research regards the world as being outside of themselves. The purpose is to gain an understanding about the social world (Almalki, 2016). The qualitative approach gains a perspective of issues by investigating them in their own specific setting. The purpose is to observe occurrences and bring meaning to them (Almalki, 2016). The differences between quantitative and qualitative research is as follows:
(Almalki, 2016). References Almalki, S. (2016). Integrating Quantitative and Qualitative Data in Mixed Methods Research – Challenges and Benefits. Ozawa, S. & Pongpirul, K. (2014). 10 best resources on…mixed methods research in health systems. Re: Topic 1 DQ 1The delivery of healthcare is becoming more complex as evidence by the rising number of individuals with comorbidities and the shift towards the quality of care versus quantity. Addressing challenges that are generated by this complex system requires research that not only produces statistical data, but also understands a population’s natural setting and provides insight how he research can be applied to that setting. Mixed methods research is becoming an important approach in generating public health evidence because it combines both qualitative and quantitative research. Qualitative research answers clinical question regarding meaning and quality improvement and provides descriptive data while quantitative research answers clinical question regarding therapy, etiology, diagnosis, prevention, and prognosis and produces numerical data (Winona State University, 2014). Favorable characteristics of mixed method research include consistency between the research question, purpose and methodological choices; verifiable and transparent techniques that demonstrate trustworthiness; potential for replicability; opportunity for self-correction; and ability to explain the phenomena under investigation (Newman and Hitchcock, 2012). Furthermore, benefits to mixed methods include answering questions that qualitative or quantitative research cannot answer alone; provides better understanding of connections or contradictions between qualitative and quantitative data; it gives participants an opportunity to have a voice and share the experience across the research process [which is important within public health]; it facilitates different avenues of exploration that enhance the quality of evidence and enables questions to be answered more deeply (Shorten & Smith, 2017). A mixed method approach uses the combine strengths of qualitative and quantitative data. Its unique design is appropirate to addressing complex public health issues.Hitchcock, J. H., & Newman, I. (2012). Applying an Interactive Quantitative-Qualitative Framework. Human Resource Development Review, 12(1), 36–52. https://doi.org/10.1177/1534484312462127Shorten, A., & Smith, J. (2017). Mixed methods research: expanding the evidence base. Evidence Based Nursing, 20(3), 74–75. https://doi.org/10.1136/eb-2017-102699Winona State University. (2014). Research Hub: Evidence Based Practice Toolkit: Levels of Evidence. Retrieved from Winona.edu website: https://libguides.winona.edu/c.php?g=11614&p=61584
1 DQ 2Topic One, Discussion Question 2:Statistics are ways to summarize data in a way that will answer a specific question (Corty, 2016). There are several key words that help with defining statistics, such as population, sample, parameter and statistic.During investigation studies researchers look for subjects to study. These subjects from large groups called a population (Corty, 2016). If the research only wanted to look at a small group of this population, they would call that a sample (Corty, 2016).For example – If I were to do a research study on obesity, I could use the state of Kentucky as my population. However, if I wanted to only look at Shelbyville, Kentucky that would be a sample of Kentucky.Data from either the sample or the population which can be reduced to a simple number like an average to summarize the group (Corty, 2016). If it is characterizing the sample, it is called a statistic; if it is characterizing the population it is called a parameter. Sample statistics use Latin letters as their symbol and population parameters use Greek letters (Corty, 2016).Then there is descriptive and inferential statistics. Descriptive is the summary statement about the set of cases (Corty, 2016). It reduces a set of data to a meaningful value to describe the characteristics of the group being observed – for example: 63% of the class were females. Inferential statistics uses a sample of cases to draw a conclusion about the larger population and reduces the data down to a single value that inferences about the population (generalization from the sample to a population – for example: Students who are female at GCU have a 15% higher GPA on average than males (Corty, 2016).Public health researchers often limit or rather stop their analyses to descriptive statistics—reporting frequencies, means and standard deviation (Guetterman, 2019). This allows for missed opportunities for more advanced analyses. “For example, knowing that patients have favorable attitudes about a treatment may be important and can be addressed with descriptive statistics. On the other hand, finding that attitudes are different (or not) between men and women and that difference is statistically significant may give even more actionable information to healthcare professionals” (Guetterman, 2019). This missing piece about differences can be addressed through inferential statistical tests (Guetterman, 2019). Therefore, both are extremely important to public health research. Part 1:Complete the following steps in both Excel and IBM SPSS Statistics. - Calculate mean, median, and mode for the variables “Annual Income” and “Age.” Show the appropriate summary tables for these measures from both Excel and SPSS. Include the other descriptive statistics that are a part of the summary output in Excel and SPSS.
- Create histograms to show the distribution for “Annual Income” and “Age.” Copy and paste the histograms from Excel and export the histogram from SPSS into the Word document for this assignment.
- Create frequency tables that include counts and percentages for smoking status, employment status, exercise level, and education level. Show the tables in the Word document for this assignment.
Based upon the Part 1 activities, write a 250-500 word interpretation that addresses the following. - Discuss the sampling strategy used in this study and if it resulted in a representative sample.
- Discuss what you are able to ascertain about the sample from the descriptive statistics.
- Explain what other variables the research team could have included to gain a better understanding of the population.
Submit one Word document for the Part 1 assignment content and a second Word document for Part 2 of the assignment. APA style is not required, but solid academic writing is expected. You are not required to submit this assignment to LopesWrite. |

For this assignment, students will utilize Excel and SPSS Statistics and the “Example Dataset.”

Using the “Example Dataset,” complete the following:

- Based on a normal distribution curve, calculate the probability of an individual being 60 years or older in this population. Show the Excel and SPSS formulas or your hand calculations. Include screenshots as needed to illustrate this.
- Using the sample standard deviation of age as an estimate of the population standard deviation, calculate by hand the standard error of the mean. Show your calculations and the answer.
- Calculate by hand a 95% confidence interval for “Age” based on the sample mean. Use SPSS to verify your answer. Include your calculations and screenshots of the SPSS output.
- Interpret the confidence interval for age and explain the three pieces of information needed to calculate a confidence interval.

Submit one Word document that includes all of the assignment deliverables.

APA style is not required, but solid academic writing is expected.

You are not required to submit this assignment to LopesWrite.

## Topic 2 DQ 1 |

P-values and confidence intervals are both used in hypothesis testing. Explain three reasons why it may be preferable to report a confidence interval over a P-value. Provide a specific example to justify your reasons.

**Topic 2 DQ 1**

De Prel et al. (2009) study found the following: P-values in scientific studies are used to determine whether a null hypothesis formulated before the performance of the study is to be accepted or rejected. In exploratory studies, p-values enable the recognition of any statistically noteworthy findings. Confidence intervals provide information about a range in which the true value lies with a certain degree of probability, as well as about the direction and strength of the demonstrated effect. This enables conclusions to be drawn about the statistical plausibility and clinical relevance of the study findings. It is often useful for both statistical measures to be reported in scientific articles, because they provide complementary types of information (p.335).

According to de Prel et al. (2009) “For example, there might be no difference between two antihypertensives with respect to their ability to reduce blood pressure. The alternative hypothesis (H_{1}) then states that there is a difference between the two treatments. This can either be formulated as a two-tailed hypothesis (any difference) or as a one-tailed hypothesis (positive or negative effect). In this case, the expression “one-tailed” means that the direction of the expected effect is laid down when the alternative hypothesis is formulated (p.335).

Reference

du Prel, J. B., Hommel, G., Röhrig, B., & Blettner, M. (2009). Confidence interval or p-value?: part 4 of a series on evaluation of scientific publications. *Deutsches Arzteblatt international*, *106*(19), 335–339. doi:10.3238/arztebl.2009.0335

**Topic 2 DQ 2**

The Central Limit Theorem is the fundamental theorem of statistics. In a nutshell, it says that for independent and identically distributed data whose variance is finite, the sampling distribution of any mean becomes more nearly normal (i.e., Gaussian) as the sample size grows (Chang, Wu, Ho and Chen, 2008). The sample mean ¯xn will then approach the population mean µ, in distribution. More formally, where N (0, 1) is the normal distribution and the symbol “d” in the equality means in distribution. σn is the standard deviation of a sampling distribution, σ is the standard deviation of the entire population the study (and which is often not known), and n the sample size. So, sample means vary less than individual measurements. (The square of the standard deviation is the variance.). The sampling distribution is a notional (imaginary) distribution from a very large number of samples, each one of size n, which approaches a normal distribution in the limit of large n. In practice, the Central Limit Theorem holds for n as low as 30, unless there are exceptional circumstances—e.g., when the population distribution is highly skewed—in which case higher values are needed. So, σn measures how widely the sample means of size n vary around the population mean µ (which is approached in the limit of large n). As expected, the results suggest that the distribution of the sample mean better approximates the normal distribution as the sample size increases. The results indicate that the true distribution of the sample mean when the sample is taken from a highly skewed distribution better approximates the normal distribution as the thickness of the tail of the population distribution increases.

Chang, H. J., Wu, C. H., Ho, J. F., & Chen, P. (2008). On sample size in using central limit theorem for gamma distribution

## Topic 3: Hypothesis Testing

- Evaluate the importance of hypothesis testing in statistics and public health research.

## Hypothesis Testing |

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