# 36-613 · Data Visualization **Meetings:** August 24–October 9, 2026 · Mondays and Wednesdays · 9:30–10:50 a.m. · Baker Hall 140A **Mini-course length:** 7 weeks, 2 sessions per week **Teaching data:** NOAA Storm Events, with optional HURDAT2 and enrichment data **Final-project data:** global data, AI, and machine-learning salary archive, 2020-2025 **Final product:** client-ready workforce-compensation and recruiting report > **Two-dataset structure:** NOAA stays in the lectures and checkpoints. The final > project uses a separate compensation archive for an executive-search client. ## Course Goal This course is about making visual analyses that help someone decide what to do. We will use R, ggplot2, and Quarto to audit public data, choose graphics that fit the question, support visual claims with statistical evidence, and explain results to a non-technical client. NOAA Storm Events supplies our shared classroom examples; the final report uses the separate workforce-compensation archive. ## Week 0 · Setup and Starter Data Complete before the first meeting. **Materials** [Lab 00 · RStudio Setup](resources/getting-started.html) **Topics** - R, RStudio, Quarto/R Markdown. - Project folders and reproducibility. - Loading NOAA Storm Events. - What one row means. You should finish with a rendered document that reports the data dimensions, lists event types, and includes one plot. ## Week 1 · Aug 24–28 · Foundations and Categorical Data **Meetings** - **Mon Aug 24** · *remote* · [Why visualize? Tidy data and the grammar of graphics](slides/week1-lecture1.html) · [source](slides/week1-lecture1.qmd) - **Wed Aug 26** · *asynchronous, recorded* · [Principles and 1D categorical data](slides/week1-lecture2.html) · [source](slides/week1-lecture2.qmd) **Topics** - Visualization as client communication. - Tidy data and the grammar of graphics with `ggplot2`. - Nominal versus ordinal categories; factor level order. - Counts, proportions, and sampling uncertainty. **Homework** HW1 opens Sun Aug 23 · [`homework-01.qmd`](assignments/homework-01.qmd) · [PDF](assignments/output/pdf/homework-01.pdf) ## Week 2 · Aug 31–Sep 4 · Categories to Distributions **Meetings** - **Mon Aug 31** · [Two categorical variables and one quantitative variable](slides/week2-lecture03-categories-to-quantities.html) · [source](slides/week2-lecture03-categories-to-quantities.qmd) - **Wed Sep 2** · [Quantitative distributions and density](slides/week2-lecture04-distributions.html) · [source](slides/week2-lecture04-distributions.qmd) **Topics** - Two-way tables, mosaic plots, and heatmaps. - Histograms, boxplots, ECDFs, and density estimates. - KS tests, violin, and ridge plots. **Homework** HW1 due Tue Sep 1 · HW2 opens Sun Aug 30 · [`homework-02.qmd`](assignments/homework-02.qmd) · [PDF](assignments/output/pdf/homework-02.pdf) ## Week 3 · Sep 7–11 · Two Quantitative Variables **Meetings** - **Mon Sep 7** · no class, Labor Day - **Wed Sep 9** · [Trends, residuals, and overplotting](slides/week3-lecture05-two-quantitative.html) · [source](slides/week3-lecture05-two-quantitative.qmd) **Topics** - Regression, fitted trends, and residuals. - Two-dimensional density, contours, and hexbins. **Homework** HW2 due Tue Sep 8 · HW3 opens Sun Sep 6 · [`homework-03.qmd`](assignments/homework-03.qmd) · [PDF](assignments/output/pdf/homework-03.pdf) ## Week 4 · Sep 14–18 · High-Dimensional Data **Meetings** - **Mon Sep 14** · [Seeing many variables](slides/week4-lecture06-many-variables.html) · [source](slides/week4-lecture06-many-variables.qmd) - **Wed Sep 16** · [Distance, MDS, and PCA](slides/week4-lecture07-distance-pca.html) · [source](slides/week4-lecture07-distance-pca.qmd) **Topics** - Pairs plots, correlations, and heatmaps. - Distance, multidimensional scaling, and principal components. **Homework** HW3 due Tue Sep 15 · HW4 opens Sun Sep 13 · [`homework-04.qmd`](assignments/homework-04.qmd) · [PDF](assignments/output/pdf/homework-04.pdf) ## Week 5 · Sep 21–25 · Embeddings, Time, and Space **Meetings** - **Mon Sep 21** · [Nonlinear embeddings and trends](slides/week5-lecture08-embeddings-trends.html) · [source](slides/week5-lecture08-embeddings-trends.qmd) - **Wed Sep 23** · [Time-series structure and spatial foundations](slides/week5-lecture09-time-and-space.html) · [source](slides/week5-lecture09-time-and-space.qmd) **Topics** - t-SNE interpretation and stability. - Daily and monthly seasonality; lags, smoothing, and autocorrelation. - Point versus areal spatial data and projection. **Homework and assessment** HW4 due Tue Sep 22. Occasional brief checkpoints; no additional full homework from this point on. ## Week 6 · Sep 28–Oct 2 · Maps, Design, and Text **Meetings** - **Mon Sep 28** · [Areal maps and graphic design](slides/week6-lecture10-maps-and-design.html) · [source](slides/week6-lecture10-maps-and-design.qmd) - **Wed Sep 30** · [Text as data](slides/week6-lecture11-text-data.html) · [source](slides/week6-lecture11-text-data.qmd) **Topics** - Choropleths, normalization, and map joins. - Event narratives as text data; word frequency, TF-IDF, or sentiment when useful. - Titles that state findings; annotation, accessibility, color, and chart critique. **Assessment** Occasional brief in-class checkpoints. ## Week 7 · Oct 5–9 · Animation, Critique, and Client Communication **Meetings** - **Mon Oct 5** · [Animation and interaction](slides/week7-lecture12-animation-interaction.html) · [source](slides/week7-lecture12-animation-interaction.qmd) - **Wed Oct 7** · topic to be announced **Focus** We will compare static, animated, and interactive displays, practice evidence-based critique, and work on the recommendation, evidence, caveats, and next action in the final client report. See [`final-project.md`](final-project.html) and [`project-rubric.md`](project-rubric.html). ## Assignments | Assignment | Opens | Due | Main Deliverable | |---|---|---|---| | HW1 · Categorical displays | Sun Aug 23, 12:00 a.m. | Tue Sep 1, 11:59 p.m. | Marginal and two-way graphics + data caveat | | HW2 · Quantitative distributions | Sun Aug 30, 12:00 a.m. | Tue Sep 8, 11:59 p.m. | Histograms, ECDF, density, and conditional comparison | | HW3 · Two quantitative variables | Sun Sep 6, 12:00 a.m. | Tue Sep 15, 11:59 p.m. | Trend, residual, contour, and binned displays | | HW4 · High-dimensional data | Sun Sep 13, 12:00 a.m. | Tue Sep 22, 11:59 p.m. | Correlation, profile heatmap, and PCA | | Critique 1 · Piazza visualization post | Course start | Fri Sep 11, 11:59 p.m. | Evidence-based visualization critique | | Critique 2 · Piazza visualization post | After Critique 1 | Wed Oct 7, 11:59 p.m. | Evidence-based visualization critique | | Final · Workforce compensation client report | Course start | Fri Oct 9, 11:59 p.m. | One self-contained HTML report with recruiting playbook and reproducibility appendix | All homework times are Eastern. Instructions and course materials are released on the teaching website. Open each Gradescope assignment from Canvas; submit homework as PDFs and the final project as one self-contained HTML file. Canvas contains official announcements, summary grades, solutions, and other restricted materials; Piazza hosts course questions and the two visualization critiques. ## Final Project Requirements The workforce-compensation report must include: - 6-10 graphics. - At least three client questions. - At least three foundational graphics from the first half of the course. - At least three advanced graphics from the second half of the course. - No more than two one-variable plots. - No more than three plots of the same type. - At least one formal statistical analysis, model summary, or uncertainty display. - A target employer and recruiting playbook. - A visible audit of duplicates, coverage, provenance, and unsupported market claims. - Clear recommendations, caveats, and future evidence requests. ## How this course differs from 36-614 The 36-613 final project is separate from the two engineering projects in 36-614. This course grades the workforce-compensation report; the second mini-course covers databases, SQL, pipelines, and system handoffs.