Quantitative Methods: Correlations Discussion: Correlations How many commercials or ads have you seen that state, “Breakfast is the most important meal of the day!” or that “Children who eat a nutritious breakfast earn better grades in school”? Research studies do indicate such a correlation; however, how could you as a researcher be certain that eating a balanced breakfast is related tochildren performing well academically? Perhaps parents who make sure their children eat a healthy breakfast are more likely to help their children with their schoolwork. Or perhaps the types of children who choose more wholesome breakfast foods are simply smarter or more motivated in school than their counterparts who prefer inadequate or unhealthy breakfasts. This week focuses on statistical methods that examine correlation. You explore how the correlation statistic is utilized in health care and evidence-based nursing practice as a means of examining relationships. You also consider the process of reporting your research results based on statistical significance, correlation, and the risk or possibility of error in your study. Learning Objectives Students will: Construct a meaningful research question and hypothesis appropriate for a correlational statistic Analyze, interpret, and report bivariate statistics Does caffeine cause cancer? Is autism caused by childhood immunizations? What is the relationship between eating sugary sweets at night and weight gain? It is often helpful to determine and explore relationships between variables. This is especially important in health care, a field dedicated to providing quality care for patients and improving health outcomes. Examining relationships between variables forms the basis for correlational statistics. In this Discussion, you identify a health care or nursing practice problem that can be explored with correlational statistics and formulate a research question for exploring that problem. You also develop a null and alternate hypothesis, determine the variables related to the study, and predict relationships between the variables based on what you know of correlational statistics. 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 Day 3 Post a cohesive response that addresses the following: Identify your selected problem in the first line of your posting and post your research question. 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. 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? Correlations Does caffeine cause cancer? Is autism caused by childhood immunizations? What is the relationship between eating sugary sweets at night and weight gain? It is often helpful to determine and explore relationships between variables. This is especially important in health care, a field dedicated to providing quality care for patients and improving health outcomes. Examining relationships between variables forms the basis for correlational statistics. In this Discussion, you identify a health care or nursing practice problem that can be explored with correlational statistics and formulate a research question for exploring that problem. You also develop a null and alternate hypothesis, determine the variables related to the study, and predict relationships between the variables based on what you know of correlational statistics. 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 Day 3 Post a cohesive response that addresses the following: Identify your selected problem in the first line of your posting and post your research question. 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. 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 Storage., D. (2019). What are correlations? Retrieved from https://www.youtube.com/watch?v=HnetU9VnpmQ Required Readings Gray, J.R., Grove, S.K., & Sutherland, S. (2021). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Saunders Elsevier. Chapter 23, “Using Statistics to Examine Relationships” Chapter 23 explains how to use statistics to examine relationships between groups using correlational analyses, scatter diagrams, Spearman rank-order correlation coefficient, and Kendall’s tau. Statistics and Data Analysis for Nursing Research Chapter 4, “Bivariate Description: Crosstabulation, Risk Indexes, and Correlation” (pp. 59–61 and 68–78) This chapter describes components of bivariate descriptive statistics, including crosstabulation, risk indexes, and correlation. The chapter also discusses the concepts of absolute risk, relative risk, odds ratio, and correlation matrices. Chapter 9, “Correlation and Simple Regression” (pp. 197–209) This portion of Chapter 9 continues the discussion of inferential statistics and explores correlation and simple linear regression.