Statistical Analysis Tools

Overview

I use multiple applications for data and statistical analysis. I started using SPSS while at Miami University in the 1990s. It remains my preferred tool for traditional statistical analysis. I'm also proficient in SAS JMP, R, and Python for various analytical needs.

I use the desktop versions of all three traditional tools, while lately spending most of my time with R and Python. I particularly enjoy working with Anaconda for Python development. I've published results from a credit scoring model built in R.

SPSS Examples

SPSS Statistics remains a powerful tool for statistical analysis with its intuitive interface.

The data screen in SPSS Statistics 25 — Click to enlarge

The output screen in SPSS Statistics 25 — Click to enlarge

SAS JMP Examples

SAS JMP provides interactive statistical discovery with dynamic data visualization.

SAS JMP data exploration interface — Click to enlarge

Statistical analysis output in SAS JMP — Click to enlarge

R Examples

I use RStudio to manage projects and Rattle for rapid data mining and analysis.

RStudio notebook for reproducible research — Click to enlarge

Python Examples

I use Anaconda for managing Python projects, providing a comprehensive data science platform.

Anaconda Navigator for Python environment management — Click to enlarge

Tools at a Glance