Project 1 Introduction: Social Security and Medicare Trust Funds Deficit Concern

Executive Summary

The Data Analytics Research and Prediction Project Demonstration course is suitable for readers that have various levels of knowledge about Data Science, Business, Economics, Statistics, and U.S. Government’s Budget interests.  The Social Security and Medicare Trust Funds Deficit Concern Project includes information, visualizations, and interpretations that provides more clarity about the effects that the various economic component variables impose on the U.S. Federal Government’s Deficit or the Economic State Target variable over time between 2001 – 2016.

The main reason that I became more interested in the Social Security and Medicare Trust Funds Deficit Concern issue was my lack of advance knowledge about the Economics subject, which is why I thought that it would make an excellent historical economics statistics topic selection for my 2019 University of Maryland University College (UMUC) M.S. Data Analytics Capstone course’s Data Science Analytical Predictive Analysis Project. Also, I have often wondered what the big fear was about concerning the National Deficit which I felt that the Government would eventually resolve income and consumption issues.

The Statistical Machine Learning Analysis Techniques used for exploration and clarification of the project’s expectations include Tableau 2019.1, SAS® Enterprise Guide 7.1, SAS® Enterprise Miner 14.3, and Microsoft Excel (i.e., descriptive statistics, correlations, forecasting, and predictions).

The problem is that the historical Social Security and Medicare Trust Funds deficit issue is complex and involves difficult economics components which available online data sets are limited due to accessibility.  The U.S. Federal Government’s Trust Fund accounts or programs were created by the U.S. Treasury Department:  The Social Security Trust Fund is operated by the Office of the Chief Actuary and the U.S. Federal Government Medicare Trust Fund is operated by the Department of Health and Human Services.   The original full Data Analysis Report was written and presented over a 12 Weeks duration using the aid of six data analysis template deliverables and three PowerPoint Presentations.

The Data Science study helped me to understand more about how the selected data variables or economic components contribute to the National Economic State or Deficit, which my SAS® Enterprise Miner 14.3 Prediction Dialog Flow Model reports on which economic component variables are most important for predicting the deficit from the Time Range of 2001 – 2016.

The Data Science study helped me to understand more about how the selected data variables or economic components contribute to the National Economic State, which my SAS® Enterprise Miner 14.3 Prediction Dialog Flow Model reports on which economic component variables are most important for predicting the deficit from the Time Range of 2001 – 2016 (See Portfolio Menu Link:  Social Security and Medicare Trust Funds Deficit Concern Project or Project 1).

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