Insights

A working timeline.

Practical notes on statistical practice, modeling, and analytical tooling — in the order they happened.

  1. 2025

    1. Data viz

      Effective Data Visualizations for DataFest

      A practical guide to picking and designing high-impact visualizations under the time pressure of ASA DataFest.

    2. Quarto

      Pre-Workshop Setup: Quarto + GitHub Pages

      Install checklist for attendees of a Quarto + GitHub Pages workshop — Git, GitHub, PATs, RStudio.

  2. 2024

    1. Statistics Lab

      Interactive Teaching with webR

      Run live R in the browser, no install required — and rebuild your data-wrangling lab around immediate feedback.

  3. 2023

    1. ML

      Symptom Severity Classification

      Python Random Forest mapping symptom flags to mild / moderate / severe ratings, with extracted rules for clinician review.

    2. ML

      Predicting $50K+ Salaries

      Team ML project on the OpenML census data — PCA feature selection plus a tuned Random Forest reaching kappa 0.95.

    3. ML

      Customer Return Forecasting

      Feature-engineered Random Forest that lifted return prediction from AUC 0.625 to 0.98 on retail data.

    4. ML

      Pinot Province Prediction

      NLP-flavored Random Forest that infers a Pinot Noir's province of origin from a critic's tasting notes.

  4. 2022

    1. Statistics

      U.S. Healthcare Spending, 1980–2014

      Longitudinal analysis of U.S. healthcare expenditure by category, region, and state across 35 years.

    2. Statistics

      The Real Cost of Smoking: Health Insurance Premiums

      Quantifying how smoking and BMI drive up insurance premiums by age and gender, in Python.

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