Health Medical Homework Help

Throughout this course, you have practiced various skills that will allow you to identify, procure, and manipulate biosurveillance and secondary data. As addressed in previous sections, public health information needs are constantly growing, and the statistical analysis of data is just one step in this process. Decisions based on this information would rely not only on the accuracy of your analysis but also on the organization of its presentation.

This week for your Scholar-Practitioner Project you will conduct descriptive and inferential analyses using your selected data set, your prepared database from Week 8, and SPSS.

To prepare:

• Review this week’s Learning Resources

, submit interpretation for your statistical analysis based on your selected data set, your prepared database, and SPSS. Mark sure to perform the following tasks for each of your research questions separately:

• Provide interpretation for descriptive statistical analyses based on your SPSS output.
• Summarize the numerical results with descriptive analysis tables or graphs, including your interpretation.
• Provide interpretation of your inferential statistical analyses using SPSS outputs.
• Summarize the numerical results with inferential analysis tables or graphs, including your interpretation.
• Provide full answer and interpretation for each of your research question(s).
• Follow APA guidelines.

Required Readings

Kamin, L. F. (2010). Using a five-step procedure for inferential statistical analyses. The American Biology Teacher, 72(3), 186–188.

Maiti, T. (2005). Tutorials in biostatistics, vol. 1: Statistical methods in clinical studies / tutorials in biostatistics, vol. 2: Statistical modelling of complex medical data. Journal of the American Statistical Association, 100(472), 1468–1468.

Marshall, G., & Jonker, L. (2010a). A concise guide to descriptive statistics. Synergy, 22–25.

Marshall, G., & Jonker, L. (2010b). A concise guide to inferential statistics. Synergy, 20–24.

McHugh, M. L. (2003a). Descriptive statistics, part I: Level of measurement. Journal for Specialists in Pediatric Nursing, 8(1), 35–37.

McHugh, M. L. (2003b). Descriptive statistics, part II: Most commonly used descriptive statistics. Journal for Specialists in Pediatric Nursing, 8(3), 111–116.

Silva-Ayçaguer, L. C., Suárez-Gil, P., & Fernández-Somoano, A. (2010). The null hypothesis significance test in health sciences research (1995–2006): Statistical analysis and interpretation. BMC Medical Research Methodology, 10(1), 44.

Thebane, L., & Akhtar-Danesh, N. (2008). Guidelines for reporting descriptive statistics in health research. Nurse Researcher, 15(2), 72–81.

Wolverton, M. L. (2009). Research design, hypothesis testing, and sampling. The Appraisal Journal, 77(4), 370–382.

Optional Resources

Bingenheimer, J. B., & Raudenbush, S. W. (2004). Statistical and substantive inferences in public health: Issues in the application of multilevel models. Annual Review of Public Health, 25, 53–77.

Diez-Roux, A. (2000). Multilevel analysis in public health research. Annual Review of Public Health, 21, 171–192.
Note: Retrieved from the Walden Library databases.

Forthofer, R. N., Lee, E. S., & Hernandez, M. (2007). Biostatistics: A guide to design, analysis, and discovery. Amsterdam, Netherlands: Elsevier Academic Press.

• Chapter 3, “Descriptive Methods”
• Review: Chapters 8–15

Gruber, F. A. (1999). Tutorial: Survival analysis—A statistic for clinical, efficacy, and theoretical applications. Journal of Speech, Language, and Hearing Research, 42(2), 432–447.
Note: Retrieved from the Walden Library databases.

Lee, E. T., & Go, O. T. (1997). Survival analysis in public health research. Annual Review of Public Health, 18, 105–134.

Levy, P. S., & Stolte, K. (2000). Statistical methods in public health and epidemiology: A look at the recent past and projections for the next decade. Statistical Methods in Medical Research, 9(1), 41–55.

Peace, K. E., Parrillo, A. V., & Hardy, C. J. (2008). Assessing the validity of statistical inferences in public health research: An evidence-based ‘best practices’ approach. Journal of the George Public Health Association, 1(1),10–23. Retrieved from http://faculty.mercer.edu/thomas_bm/documents/jgph…

Rutledge, T., & Loh, C. (2004). Effect sizes and statistical testing in the determination of clinical significance in behavioral medicine research. Annals of Behavioral Medicine, 27(2), 138–145.