Turn your homework into an ioslide presentation.
This is an HTML R Markdown document that provides a reference for week 2's homework for students in University of Cincinnati's Data Wrangling with R class.
This analysis provides an example final project for students in the University of Cincinnati's Data Wrangling with R class.
This is an HTML R Markdown document that provides a reference for week 1's homework for students in University of Cincinnati's Data Wrangling with R class.
This R Markdown tutorial is an example provided to my R programming students who are tasked to try replicate the document on their own.
This repository accompanies the research paper “Unpacking the United States Air Force’s Little Blue Book(s)” submitted for inclusion in the Proceedings of the 2016 Industrial and Systems Engineering Research Conference. Due to the constrained page limit for submissions this year the methodology section for the submitted paper was greatly truncated. This file expands the methodology section to provide a more robust understanding of the approach applied. Furthermore, this repository contains the code scripts employed in the analysis and the text analyzed.
Data processing with dplyr & tidyr
This is a tutorial I provided at Wright State University on data wrangling with the dplyr & tidyr packages.
Provides a tutorial for the visual graphic illustrating the growth trends of median incomes in the United States.
Provides a step-by-step approach to creating the Dayton temperature visualization, which mirrors the illustration in Edward Tufte's classic book Visual Display of Quantitative Information
This presentation highlights a word prediction algorithm and Shiny application product
This report provides an update on the text mining and prediction project for the Data Science Specialization capstone
This project fulfills a requirement in the Practical Machine Learning course offered by Johns Hopkins for their Data Science Certification via Coursera. In this project, I use data from accelerometers on the belt, forearm, arm, and dumbell of 6 participants and apply a Random Forest modeling technique to accurately predict the manner in which they did the exercise.
This project involves exploring the U.S. National Oceanic and Atmospheric Administration’s (NOAA) storm database. This database tracks characteristics of major storms and weather events in the United States, including when and where they occur, as well as estimates of any fatalities, injuries, and property damage. The raw data consists of 37 variables with 902,297 observation from years 1950-2011. This research identifies which storm events have the greatest health consequences and which storm events have the greatest economic consequences at the aggregate level.