Workshop Overview

Modern operations move fast; information moves faster. This workshop helps U.S. and NATO personnel turn raw data into clear, defensible insights using R and RStudio—without heavy programming. We focus on the parts of R that speed up decision support: clean data quickly, visualize clearly, summarize reliably, and produce repeatable reports.

No prior coding required. We use sanitized, unclassified defense-style datasets (logistics, readiness, geospatial context) and emphasize practical judgment, not buzzwords. Each day ends with Q&A and an optional office-hour block for extra help.

Learning Objectives

Use R and RStudio to import, clean, join, and validate mission-relevant data.
Apply the tidyverse to summarize, reshape, and visualize information quickly.
Build clear charts and maps that support briefings and after-action reviews.
Produce repeatable, parameterized R Markdown/Quarto reports.
Run and interpret light-weight models (trend, regression, simple classification) for planning.
Follow good practices for reproducibility, OPSEC, and handoff to teammates.

Prerequisites

Familiarity with defense or government operations helpful
Comfortable with spreadsheets; no prior coding required

Target Audience

Analysts, planners, logisticians, intelligence personnel
Defense contractors and federal program managers
Technical staff seeking a fast on-ramp to R

Development Environment

R (≥ 4.3) and RStudio (Posit Desktop)
Packages: tidyverse, readxl, janitor, lubridate, arrow, sf, ggplot2, tmap or leaflet, broom, knitr, rmarkdown, quarto
Offline-friendly docs; sanitized CSV/Parquet datasets provided

Agenda (5 Days)

Day 1 – Foundations & Setup

Orientation (30m): What “decision support with R” means in practice; success criteria for your role.
R & RStudio Tour (60m): Console, scripts, projects, file hygiene, working directories.
Data In, Clean, and Ready (2h): Import CSV/Excel/Parquet; fix headers with janitor; parse dates with lubridate; handle missingness.
Tidyverse Basics I (90m): dplyr verbs, grouping/summarizing; quick quality checks to catch bad data early.
Mini-Lab (30m): Clean a logistics dataset and produce a 1-page EDA summary.

Outcome: A clean R project, reproducible script, and first visuals.

Day 2 – Wrangling Deep Dive & Visualization

Tidyverse Basics II (90m): Joins, keys, cross-checks; rowwise vs. vectorized ops; pitfalls and fixes.
Reshape & Compare (60m): pivot_longer/wider; building tidy tables for side-by-side readiness comparisons.
Visual Basics with ggplot2 (90m): Lines, bars, densities; faceting; labeling and theme choices for briefs.
Design for Decision Makers (60m): Clarity vs. complexity; encoding choices; avoiding chartjunk.
Lab (30m): Turn wrangled tables into 2–3 briefing-quality charts.

Outcome: A tidy analysis pipeline and a small chart pack suitable for leadership slides.

Day 3 – Time, Trend, and Geospatial

Time & Trend (75m): Time-based summaries, rolling means, simple change detection; communicating uncertainty.
Geospatial Foundations (90m): sf basics, CRS/projections, simple choropleths; routes/areas (unclassified).
Operational Maps (60m): tmap vs. leaflet; static vs. interactive choices for exercises/briefs.
Reporting I (45m): R Markdown/Quarto basics, structure, chunk options, inline values, kable tables.
Mini-Exercise (30m): Add a time-series panel and a simple map to your report.

Outcome: A report that blends trend + map views and rebuilds on new data.

Day 4 – Reporting, Parameters & Modeling Lite

Reporting II (75m): Parameters, child docs, reusable templates; producing HTML/PDF variants.
Reproducibility & Handoff (45m): Projects, file structure, relative paths, minimal versioning (Git optional).
Modeling Basics (75m): Linear/logistic regression; when simple beats complex; feature hygiene.
Fit, Check, Explain (60m): broom tidiers; confidence vs. prediction intervals; practical interpretation.
Scenario Workshop (45m): Build a parameterized brief that toggles between units/regions/time windows.

Outcome: A parameterized report plus an interpretable “risk/trend” model you can explain in one slide.

Day 5 – Capstone Build & Brief

Predict then Plan Lab (60m): Example: predict delay risk; translate to an action option; sensitivity checks.
Capstone Build (120m): Team project: data → wrangle → visuals (incl. map) → small model → parameterized report.
Brief & Peer Review (60m): 5-minute briefs; peers stress-test assumptions and clarity.
Next Steps (30m): Packaging your work, small pilots, sustainment.

Outcome: A concise decision-support product (report + assets) ready for leadership or exercise use.

Materials Provided

Slides, step-by-step notebooks, sanitized datasets (CSV/Parquet)
Cheat sheets (tidyverse, ggplot2, geospatial quickstart)
Report templates (R Markdown/Quarto) and a small style guide

Security & Classification

All materials are unclassified; scenarios and data are sanitized for training.

Contact

To request dates or a private cohort: [email protected]