Portfolio of data projects on which I have worked. Projects in the repository include the following:

• Latino Technology Use in WA State - This project explores access to technology and technology use amongst Latina/os under 30 in Washington state. The data source for this project is the 2010 Washington State Population Survey, which includes information from 14220 observed participants measured by 267 variables. The statistical analysis is conducted in SPSS. A final written report (saved as a .pdf file) discussing my findings is included as well.
• Medicare Hosptial Data Project - This project includes three small programs written in R that mine information from an Excel file of Hospitals accepting Medicare funding in the United States. The first program, "best", returns the best ranked hospital in the Excel file from a given state as measured by a given health outcome. The second program, "rankhospital", returns the given ranking of the hospital in a given state as measured by a given health outcome. The third program, "rankall", returns a data table of a hosptials with given rank and a given outcome measurin for all fifty states and four US territories.
• PM 2.5 Pollution in the United States, 1999-2008 - This project includes eight graphs and one map displaying changes in level of PM 2.5 pollution in the United States between 1999 and 2008. The graphs and the map measure changes in overall PM 2.5 pollution, changes in PM 2.5 pollution from coal combustion, and changes in PM 2.5 pollution from motor vehciles. Some fo the graphics measure changes in the nation as a whole, while others look just at the city of Baltimore. The R scripts used to produces the eight graphs and one map are provided in the folder. The graphs and the map are saved as .png files.
• Samsung Smartphone Data Project - This project includes the R script used to convert seven .txt files drawn from an experiment measuring human movements with a Samsung Galaxy SII smartphone into an one Excel file. The .txt files are drawn from the online Machine Learning Library at the University of California at Irvine. The folder includes a copy of the original .txt files, the R script used to merge and transform these files, and the final Excel table that results from the R script.