Eco 510 Final Project Guidelines And Rubric Overview

Eco 510 Final Project Guidelines And Rubricoverviewthe Final Project F

The final project involves creating an empirical analysis advising the U.S. Department of Health and Human Services (HHS) on economic and demographic factors influencing population physical activity. The project includes research, data collection, statistical testing, analysis, and conclusions, divided into milestones across the course, culminating in a comprehensive final paper.

Paper For Above instruction

The objective of this final project is to conduct an empirical economic and demographic analysis related to leisure-time physical activity in the United States, aiming to advise HHS on policy and initiatives to promote health benefits through increased physical activity. The project spans research, data collection, statistical testing, analysis, and synthesis stages, structured to develop a comprehensive and data-driven evaluation of factors influencing physical activity levels across states and regions.

The project begins with foundational research into demographics, economic indicators, behavior related to physical activity, and health economics. Students are required to compile scholarly background information summarized in APA citations, focusing on four specific topics: demographics as predictors of health, economic indicators as predictors of health, leisure-time physical activity as a predictor, and the economics of health. These summaries should be organized in a two-column table in Microsoft Word, citing at least two scholarly sources per topic.

Subsequently, students identify and assess relevant government data sources such as the BLS, BEA, CDC, and HHS. They will create an Excel spreadsheet of relevant data at national and state levels, analyzing strengths and limitations with APA-cited support. This dataset serves as the basis for quantitative analysis and is essential for generating hypotheses about economic and demographic influences on physical activity.

Selection of statistical tools follows, including best-fit lines, central tendencies, linear regression, variances, and confidence/prediction intervals, with a justification for each. Students determine up to three predictors, such as employment, household income, education attainment, or GDP, providing reasons for their choices. A draft of these statistical tests and their rationale forms part of the submission, preparing for subsequent analysis.

Using Minitab, students perform the statistical analyses—hypothesis testing, regression modeling, and graph generation. They produce summaries, tables, and visualizations that demonstrate the relationships between selected variables and physical activity levels. Interpretation focuses on correlation, causality, and the robustness of the findings, with an emphasis on understanding the practical and statistical significance of results.

Final analysis synthesizes research and statistical findings, addressing key questions: what economic and demographic factors influence leisure activity? Which states or regions may benefit most from NEXI? Which businesses could profit from related services, and what is their potential for success? The analysis discusses limitations, confidence levels based on intervals and regression outputs, and provides insights into policy implications, regional needs, and business opportunities.

The final paper, 8-10 pages, integrates all components—research, data analysis, statistical testing, and conclusions—reflecting feedback received during milestones. Proper APA citations and a professional presentation are essential. This comprehensive report aims to equip HHS with data-driven insights to guide health initiatives and economic policies encouraging increased physical activity across the U.S.

References

• Centers for Disease Control and Prevention. (2020). Physical Activity Basics. cdc.gov.
• Bureau of Labor Statistics. (2021). Employment and Household Income Data. bls.gov.
• Bureau of Economic Analysis. (2021). Regional Economic Data. beaa.gov.
• World Health Organization. (2020). Economics of Physical Activity. who.int.
• HHS Office of the Assistant Secretary for Planning and Evaluation. (2019). Health Economics Research. hhs.gov.
• Wooldridge, J. M. (2016). Introductory Econometrics: A Modern Approach. Cengage Learning.
• Greene, W. H. (2018). Econometric Analysis. Pearson.
• Stock, J. H., & Watson, M. W. (2020). Introduction to Econometrics. Pearson.
• Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics. Pearson.
• Sharra, N., & Feeney, M. (2021). Data Analysis in Public Health Policy. Journal of Public Health, 112, 15-22.