To prepare:

- Review this week’s Learning Resources and the “Correlation” tutorial focusing on the types of research questions that can be answered using a correlational statistic.
- Brainstorm a number of health care delivery or nursing practice problems that could be explored using correlational statistics. Then, select one problem on which to focus for this Discussion.
- Formulate a research question to address the problem and that would lead you to employ correlational statistics.
- Develop a null hypothesis and alternate hypotheses.
- Ask yourself: What is the expected direction of the relationship?

**By tomorrow Tuesday 10/03/17, 5 pm, write a minimum of 550 words essay in APA format. Use the two references below from the required media and reading list.**

**Include the level one headings as numbered below:**

**Post**a cohesive response that addresses the following: 1) Identify your selected problem in the first line of your posting and post your research question. 2) Post a null hypothesis and alternate hypotheses for your research question and identify the dependent and independent variables that would be associated with the research study. 3) Provide your prediction for the expected relationship (positive or negative) between the variables. Why do you think that sort of relationship will exist? What other factors might affect the outcome?

**Required Media**Walden University. (n.d.). Correlations. Retrieved August 1, 2011, from http://streaming.waldenu.edu/hdp/researchtutorials/educ8106_player/educ8106_correlations.html

**Required Readings**

**Gray, J.R., Grove, S.K., & Sutherland, S. (2017)**

**. Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence****(8th ed.). St. Louis, MO: Saunders Elsevier.**

- Chapter 23, “Using Statistics to Examine Relationships”

*Statistics and Data Analysis for Nursing Research*

- Chapter 4, “Bivariate Description: Crosstabulation, Risk Indexes, and Correlation” (pp. 59–61 and 68–78)

- Chapter 9, “Correlation and Simple Regression” (pp. 197–209)