Data Science, Analytics & Statistics

"A problem well stated is a problem half solved." - John Dewey

Data Science & Database Administration

As Chief Technical Officer and Lead Developer for E-Laborative Technologies Ltd. I have been tasked with a variety of challenging requirements related to data storage, analysis, management, and administration. I have earned certificates in probability, inference & modeling, linear regression, wrangling, and machine learning through the HarvardX program offered through Harvard University, and I have also completed online courses related to Epidemiology offered by Johns Hopkins. I regularly employ SQL and R for big data analytics, visualization, and storage. Most of my professional work involves proprietary business data, financial and legal documentation. I also enjoy public health issues and actively work on several projects related to public health and epidemiology as a private citizen researcher.

The following statistics dashboards demonstrate some of my recent work using R to conduct exploratory data analysis related to various subjects of general public interest. These dashboards utilize various curated public repos, API's, R packages, and other known sources for data acquistion.

Coronavirus Visualization Dashboard
This dashboard shows Coronavirus stats and X day interval growth rates over bar, column and grid charts. It also offers colored chloropleth maps of the US by state, by county, and in individual state-level views. This tool incorporates data from the U.S. Census Bureau and COVID-19 stats compiled by the CoronaDataScraper project.

Costco Drive Time Isochrone
This dashboard plots drive times to costco locations along the I5 corridor in Oregon.

Restaurant Menu Calculator Program

Resources for Studies in Public Health
GIS Resources
Visualization & Graphics Developer Resources
Key Terms
  • PSM - Problem Solving Methodology
  • Conceptual Framework - A picture of the problem that includes KD's
  • KI - Key Indicator
  • KD - Key Determinants
  • OI - Outcome Indicators
  • Proximal Determinants - Most causally linked to OI
  • Distal Determinants - Less causally linked or non-modifyable determinants
  • Ecological Fallacy - When inferences about the nature of individuals are deduced from inferences about the group to which those individuals belong
  • Simpson's Paradox - When stratification reverses observed trends