Reflection Number 1
HCIN 547, Health Care Analytics, provided many opportunities to work with Microsoft Access, Structured Query Language (SQL), and Tableau. These are all applications for data sorting and management that can later be used for statistical analysis and solving problems. Collecting and cleaning the data is also a vital step preceding data sorting. Within this assignment, we were required to consolidate five (5) years of Health Resources & Services Administration (HRSA) data into one spreadsheet, identifying the data dictionary and corresponding field types such as text, numbers, etc. Finally, we were required to use preexisting queries through Microsoft Access. This prepared our data for the next step and helped position our data for the final project. The artifact I chose to attach identifies that my topic will be diabetes. Ultimately, one outcome of data management and manipulation would reveal concentrations of diabetes patients in certain parts of the U.S.
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Reflection Number 2
There are so many ways to analyze and present data. One way is to use the application of Analysis Variance (ANOVA) and simple linear regression. As the analysis is completed, the data sets may have a relationship between regression and the t-test to determine whether the hypothesis is either dependent or independent of a variable. The MSNC 507 Statistics artifact I chose is an assignment of three questions with several subdivisions. One of the exercises required working off the data of Excel worksheets and building charts with different x and y labels and values. Then, I analyzed which of the charts had a linear relationship model, which appeared to be the best and the worst, and why. This was an excellent exercise for instilling program outcomes regarding statistical analysis and selecting different tools to evaluate a problem. This artifact includes three (3) excel worksheets.
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Reflection Number 3
The final project for HCIN 543, Database Design and Knowledge Management, was a culmination of the work I did during many modules. I think it is a good example to include as an artifact since it embodies the program outcomes of spreadsheet development, managing and extrapolating data, and the use of a data management application, such as Microsoft Access. The data set I chose was university-related; however, this type of manipulation works for any healthcare-related topic. By creating my own database, I was able to organize, extract, and display data. Another aspect of this artifact was to normalize the data, eliminate any repeating groups, and update anomalies. Since I was building a relational database, repeating groups could not exist.
| hcin-543_-_final_report_-_gilda_demergian.docx |