Analyzing a Health Care Data Set

This assessment will ask you to select, apply, and interpret the results of a variety of statistical tests on a health care data set. This may include tests you have learned about or applied previously in the course, or the new nonparametic t-Test which is presented in the resources for this assessment. The challenge is using what you have learned to determine the best course of action to complete the interpretative tasks the assessment lays out for you. This attempts to mirror real-world situations where the data or statistical analysis could be approached in a variety of different ways. To decide which statistical test to use for the various dependent variables to be analyzed, one must first know more about the data type (measurement level) within those variables.

Overview Public health researchers are often involved in collaborating in the design, development, and analysis of community initiatives of varying complexity. While this course alone will not provide sufficient training for you to act as a statistical consultant, it does offer a broad and practice-based analytic foundation that can position you to better understand and more fully contribute to real-world project teams. Building on the basic statistical concepts and analytical techniques of the previous units, this assessment is an opportunity to use your cumulative quantitative-analysis skills to address a broad set of real-world research questions. Demonstration of Proficiency By successfully completing this assessment you will address the following scoring guide criteria, which align to the indicated course competencies. Competency 2: Apply appropriate statistical methods using common software tools in the collection and evaluation of health care data. Perform the most appropriate parametric or nonparametric test to answer each question. Competency 3: Interpret the results and practical significance of statistical health care data analyses. Assess the assumption of normal distribution prior to analysis.

Appropriately interpret the statistical output (such as estimate, p-value, confidence interval, and effect size) resulting from each statistical test. Summarize the clinical implications, significance, and potential limitations of the study data and outcomes. Competency 4: Assess the quality of quantitative research methods reported in peer-reviewed health care literature. Describe the practical significance of the results of statistical tests. Competency 5: Address assignment purpose in a well-organized text, incorporating appropriate evidence and tone in grammatically sound sentences. Articulate meaning relevant to the main topic, scope, and purpose of the prompt.

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