NURS 8201 Week 4 Assignment Frequency and Descriptive Statistics Walden -

NURS 8201 Week 4 Assignment Frequency and Descriptive Statistics Walden

Sample Answer for NURS 8201 Week 4 Assignment Frequency and Descriptive Statistics Walden Included After Question

Week 4: Quantitative Methods: Analyzing Quantitative Data

Research allows us to learn more. It allows us to go beyond simple questioning and curiosity. It provides us the opportunity to dig deeper, search for outcomes, and explore meaning. Throughout your practice, you will experience the need for research. Whether it is in your educational journey or within your career, research is an integral skill set for your role as a DNP-prepared nurse.
Research begins as a question which leads to the study and collection of data. Through understanding and examining variables, determining levels of measurement, and analyzing outcomes, the question presented comes into clearer focus. This week, you consider the role of research in the field of nursing. You will explore variables in research and analyze data to develop understanding and meaning.
Learning Objectives
Students will:
• Analyze independent and dependent variables for research questions
• Identify levels of measurement for independent and dependent variables
• Analyze approaches for addressing advantages and challenges in the data analysis for variables and levels of measurement
• Evaluate frequency and descriptive statistics
• Summarize descriptive statistics
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Learning Resources

Required Readings (click to expand/reduce)

Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.
• Chapter 21, “Introduction to Statistical Analysis” (pp. 635–651)
• Chapter 22, “Using Statistics to Describe Variables” (pp. 652–662)
• Chapter 26, “Interpreting Research Outcomes” (pp. 699–716)

Gholami, S., Mojen, L. K., Rassouli, M., Pahlavanzade, B., & Farahani, A. S. (2020). The predictors of postoperative pain among children based on the theory of unpleasant symptoms: A descriptive-correlational study. Journal of Pediatric Nursing, 55, 141–146. doi:10.1016/j.pedn.2020.08.006

Huang, J., Qi, H., Lv, K., Chen, X., Zhuang, Y., & Yang, L. (2020). Emergence delirium in elderly patients as a potential predictor of subsequent postoperative delirium: A descriptive correlational study. Journal of PeriAnesthesia Nursing, 35(5), 478–483. doi:10.1016/j.jopan.2019.11.009

Document: Week 4 Descriptive Statistics SPSS Output (PDF)

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Discussion: Levels of Measurement
What is the incidence of blood clots from COVID-19 in females over the age of 35?
The above question is an example of a research question. A research question consists of three parts and guides the methods and approaches in which you will study the question to find answers. The research question includes: the question, the topic, and the population or variables. In the example provided above, the question is examining the prevalence of blood clots from severe COVID-19 in a selected population. From this question, the variables can be assessed, considerations can be analyzed, and populations can be sampled in order to guide the research.

Photo Credit: Socha, A. (n.d.). Scale question, balance [Photograph]. pixabay.com. https://pixabay.com/photos/puzzle-last-part-joining-together-3223922/
During Week 2, you developed a research problem statement based on a topic of interest to you or your specific area of practice. Using this research problem statement, you will develop a research question. “A research question is a concise, interrogative statement that is worded in the present tense and includes one or more of a study’s principal concepts or variables” (Gray & Grove, 2020). These questions typically point to the type of study that will be conducted and serves as a guide for the research.
For this Discussion, reflect on your research problem statement. Consider the independent and dependent variables of your research problem through the construction of a research question. Reflect on the potential levels of measurement for your variables and the rationale for the labels, as well as consider the advantages and challenges that you might experience in the statistical analysis of your proposed variables.
Reference: Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

To Prepare:

• Review your research problem statement from Week 2 to develop your research question.
• Review the Learning Resources on how to describe variables.
• Consider the levels of measurement for your variables: nominal, ordinal, interval, or ratio.
• After reviewing your research question and considering the levels of measurement, analyze your classification for each variable. What was behind your reasoning for labeling the variables? How might the data be analyzed based on these labels?
• Consider advantages and challenges that you might encounter in the statistical analysis of your proposed variables.

By Day 3 of Week 4

Post your research question and describe the independent and dependent variables. Then, identify the level of measurement of both your independent and dependent variables. Provide a brief rationale for your classification of each variable. Be specific. Explain considerations of analyzing data related to each variable based on its level of measurement. Be sure to include any advantages or challenges that you might encounter in your statistical analysis of each variable and explain why.

By Day 6 of Week 4

Read a selection of your colleagues’ responses and respond to at least two of your colleagues on two different days by noting any discrepancies and/or suggesting alternatives in the levels of measurement and statistical analyses described.
Submission and Grading Information
Grading Criteria

To access your rubric:
Week 4 Discussion Rubric

Post by Day 3 of Week 4 and Respond by Day 6 of Week 4

To Participate in this Discussion:
Week 4 Discussion

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Assignment: Frequency and Descriptive Statistics

Imagine that you have collected data from 100 patients. You have carefully compiled vitals, pain scores, and medications for each of the patients. However, what does all of this data mean? Is your work now done?
How do we make data meaningful? Why must we move beyond the raw data to ensure that data is purposeful?
Descriptive analysis is the analysis of the data to develop meaning. Descriptive analysis provides meaning through showing, describing, and summarizing the data compiled to “reveal characteristics of the sample and to describe study variables” (Gray & Grove, 2020). This allows the researcher to present data in a more meaningful and simplified way.

Photo Credit: Getty Images

For this Assignment, summarize your interpretation of the descriptive statistics provided to you in the Week 4 Descriptive Statistics SPSS Output document. You will evaluate each variable in your analysis.
Reference: Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

To Prepare:

• Review the Week 4 Descriptive Statistics SPSS Output provided in this week’s Learning Resources.
• Review the Learning Resources on how to interpret descriptive statistics, including how to interpret research outcomes.
• Consider the results presented in the SPSS output and reflect on how you might interpret the frequency distributions and the descriptive statistics presented.

The Assignment: (2–3 pages)

• Summarize your interpretation of the frequency data provided in the output for respondent’s age, highest school grade completed, and family income from prior month.
• Note: A frequency analysis is way of summarizing data by depicting the number of times a data value occurs in the data table or output. It is used to analyze the data set including where the data are concentrated or clustered, the range of values, observation of extreme values, and to determine intervals for analysis that could make sense in categorizing your variable values.
• Summarize your interpretation of the descriptive statistics provided in the output for respondent’s age, highest school grade completed, race and ethnicity, currently employed, and family income from prior month.
• Note: The descriptive analysis includes N (size of your sample), the mean, the median, the standard deviation, the size and spread of your data to determine the variability/variance in your data.
Reminder: The College of Nursing requires that all papers submitted include a title page, introduction, summary, and references. The Sample Paper provided at the Walden Writing Center provides an example of those required elements (available at https://academicguides.waldenu.edu/writingcenter/templates/general#s-lg-box-20293632). All papers submitted must use this formatting.

By Day 7

Submit your Assignment by Day 7 of Week 4.
Submission and Grading Information
To submit your completed Assignment for review and grading, do the following:
• Please save your Assignment using the naming convention “WK4Assgn+last name+first initial.(extension)” as the name.
• Click the Week 4 Assignment Rubric to review the Grading Criteria for the Assignment.
• Click the Week 4 Assignment link. You will also be able to “View Rubric” for grading criteria from this area.
• Next, from the Attach File area, click on the Browse My Computer button. Find the document you saved as “WK4Assgn+last name+first initial.(extension)” and click Open.
• If applicable: From the Plagiarism Tools area, click the checkbox for I agree to submit my paper(s) to the Global

Reference Database.

• Click on the Submit button to complete your submission.
Grading Criteria

To access your rubric:
Week 4 Assignment Rubric

Check Your Assignment Draft for Authenticity

To check your Assignment draft for authenticity:
Submit your Week 4 Assignment draft and review the originality report.

Submit Your Assignment by Day 7 of Week 4

To participate in this Assignment:
Week 4 Assignment

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What’s Coming Up in Module 3?

Photo Credit: [BrianAJackson]/[iStock / Getty Images Plus]/Getty Images
In the next module, you will continue your exploration of quantitative research and data analysis. You will look more closely at additional techniques and methods of conducting quantitative data analysis and interpretation.
Looking Ahead: Assignment: CITI Program Training
As a doctorally-prepared nurse, you may have opportunities to collaborate in research activities in your practice. The Collaborative Institutional Training Initiative (CITI Program) provides education on protection of human subjects. In the United States, the CITI Program is the training module that most research institutions use. Therefore, as a part of this course, you are required to successfully complete the CITI Program training by Day 7 of Week 9.

Photo Credit: Андрей Яланский / Adobe Stock
This online course may take up to 8 hours to complete. You will receive an electronic Certificate of Completion upon successfully passing the training. You will submit this Certificate of Completion to the Walden University Institutional Review Board office when you submit an application to conduct research.

To Prepare

• Follow the instructions on the CITI Program Learner Registration webpage to create your account (https://www.citiprogram.org/index.cfm?pageID=154&icat=0&clear=1).
o Review the CITI Program Learner Registration Guide for step-by-step instructions on completing the registration process.
o Be sure to select Walden University under the “Select Your Organization Affiliation” section. If you do not select Walden University, you will not be able to access the training at no cost.

• Create and record your CITI Program User Name and Password for future reference.
To complete:

By Day 7 of Week 9

• Complete the five required Citi Program training modules as well as the two elective modules.
• Copy and paste the Certificate of Completion into a Word document and save the file as a “.doc” or “.rtf” file.
You are not required to submit this Assignment this week.
Note: This Assignment must be completed by Day 7 of Week 9 in order for you to successfully complete this course.
Next Module NURS 8201 Week 4 Assignment Frequency and Descriptive Statistics Walden

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A Sample Answer For the Assignment: NURS 8201 Week 4 Assignment Frequency and Descriptive Statistics Walden

Title: NURS 8201 Week 4 Assignment Frequency and Descriptive Statistics Walden

Statistical analysis is important in research as it helps in the analysis of the collected data to give important results and reveal important trends, which then helps answer research questions and draw conclusions. One of the aspects is frequency and descriptive statistics which are used in describing the main features of a dataset. Therefore, it is important for researchers to have adequate knowledge regarding data analysis using relevant statistical approaches and interpret the analyzed data to support decisions such as clinical decisions (Grey & Grove, 2020). Therefore, the purpose of this assignment is to review a provided descriptive statistics SPSS output. In addition, a summary of the interpretation of the frequency data provided for the respondent’s age, highest school grade completed, and family income will be given.

Participants’ Age

In terms of the participant’s age, the number of observations (N) is 1000. Therefore, this number of observations is adequate to represent the distribution of data since 20 observations are often considered sufficient. The maximum value is 49.43, and the minimum is 19.38. The observation is large enough to offer more precise estimates as part of the analysis and results (Mishra et al.,2019). The mean age of the respondents is 36.64, which shows that the average age of the respondents in the sample was approximately 37 years.

It is also important to explore the measures of variance. As such, the standard deviation of the respondents’ age is 6.20, which implies that the majority of the observations are spread within the standard deviations of either side of the mean (Kaliyadan & Kulkarni, 2019). The respondents’ age data is also left skewed as the value observed is -0.374. The implication is that it is slightly left-skewed. As observed from the histogram, the respondent’s age is left-skewed since most of the values fall on the left side of the histogram.

Highest High School Grade Completed

It is also important to explore the descriptive statistics for the highest grade completed. The observations observed (N) for this parameter is 989, which also implies that the values are sufficient for reporting. The mean value for the highest grade completed is 11.28, which is a measure of the average grade attended by the respondents. The measure of variance (standard deviation) observed for the highest grade completed is 1.56, which shows some variability. In addition, with normal data, the majority of the observations are spread within 0.75 standard deviations on either side of the mean. While a lower standard deviation shows a lower spread in the sampled data, a higher standard deviation shows a bigger spread in the sampled data (McGrath et al.,2020).

In terms of skewness, the data was again left skewed as the observed value was -0.73, which is lower than -1.0. This observation is supported by the shaper of the histogram on the high school grade completed, as the majority of the values fall on the left side of the histogram.

Family Income

Another analysis is on the family income. Therefore, it is also important to consider the descriptive statistics. The number of observations in the case of family income is 895. While the maximum value in terms of earnings per family is $6,593, the lowest or minimum earning is 0. The mean value for family income is $1,172.59. In terms of the measure of variance, the standard deviation value is $26.34, which is an indication of some variability in the family income. The skewness for family income is 2.03, which indicates that the family income values are positively skewed, pointing to a positively skewed distribution (Orcan et al.,2020). Indeed, this observation has been supported by the shape of the histogram on the family income, which shows the majority of the observations falling on the right side of the histogram, which is a further indication of right skewness.

Race and Ethnicity

Another important aspect of the data and analysis shown in the output is race and ethnicity. While those who identified themselves as blacks, not Hispanic, were 80.3%, Hispanics formed 12.8%. In addition, Whites, not Hispanics, were 5.3%, while those who identified themselves as other races were 1.4%. This analysis shows that most of those who gave their details were blacks; as such, conclusions made from this set of data would point more to what is happening with blacks than other races.

The other important aspect of data is the number or percentage of those who are currently employed. From the analysis, a total of 546 respondents who participated in the yes or no question to confirm their employment status confirmed that they were not employed, constituting 54.6%. The remaining 45.2%, or 452, are currently employed. Even though the number of those employed was lower than the unemployed, the difference was slight, which implies a smaller variation.

Conclusion

Descriptive statistics and frequency can play an important role in the analysis of a set of raw data to help gain a deeper insight into the data under consideration. As such, a summary of such analysis can reveal important sample features. Therefore, this analysis has focused on various data aspects such as the respondent’s age, the highest school grade completed, race and ethnicity, and employment status, that is, whether an individual is currently employed or not.

References

Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier

Kaliyadan, F., & Kulkarni, V. (2019). Types of variables, descriptive statistics, and sample size. Indian Dermatology Online Journal, 10(1), 82. https://dx.doi.org/10.4103%2Fidoj.IDOJ_468_18

McGrath, S., Zhao, X., Steele, R., Thombs, B. D., Benedetti, A., & DEPRESsion Screening Data (DEPRESSD) Collaboration. (2020). Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis. Statistical methods in medical research, 29(9), 2520–2537. https://doi.org/10.1177/0962280219889080

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://dx.doi.org/10.4103%2Faca.ACA_157_18

Orcan, F. (2020). Parametric or non-parametric: Skewness to test normality for mean comparison. International Journal of Assessment Tools in Education, 7(2), 255–265. https://doi.org/10.21449/ijate.656077

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