Data Storytelling Group Project · Guideline

Turn a focused analytical question into a clear, evidence-based story

Author
Affiliation

Byeong-Hak Choe

SUNY Geneseo

Published

November 16, 2026

Project at a glance

  • Each group will deliver a 10-minute presentation, followed by a 1–2 minute Q&A.
  • Presentation order will be determined by a random draw.
  • Every group member must contribute meaningfully and participate in the presentation.
  • If multiple groups choose the same topic, they may be scheduled in different sessions to reduce repetition.

Choose a topic

Start with the Group Project Topics catalog. Each topic page introduces the available data, important variables, possible questions, and a sensible first step.

The catalog is a set of starting points—not a list of required questions. Your group should narrow the topic into a focused question and develop its own evidence-based story.

Note

Your group may use another dataset with advance approval. Send the instructor the proposed data source and a short explanation of the question you want to investigate. Also submit any additional dataset that you combine with a suggested topic.

Build the data story

1. Frame the question

  • Give the audience enough background to understand why the topic matters.
  • State one focused project interest, problem, or question.
  • Identify the audience and the decision, action, or understanding your story should support.

2. Prepare and examine the data

  • Explain the observations and variables you selected.
  • Document important filtering, recoding, joins, and missing-data decisions.
  • Use descriptive statistics to establish context and identify meaningful patterns.
  • Verify row counts and key assumptions after major transformations.

3. Visualize the evidence

  • Use charts that match the analytical question and data type.
  • Make labels, units, legends, and comparison groups easy to understand.
  • Use color intentionally and choose a color-blind-friendly palette.
  • Remove visual elements that do not support the message.

4. Shape the narrative

A strong presentation usually follows this sequence:

  1. Context — What should the audience know?
  2. Question — What did your group investigate?
  3. Evidence — What patterns did the analysis reveal?
  4. Meaning — Why do those patterns matter?
  5. Takeaway — What should the audience remember or do next?

5. Explain significance and limits

  • Connect the findings to a practical, organizational, social, or policy context.
  • Distinguish association from causation.
  • Acknowledge relevant limitations, missing information, and uncertainty.

Deliverables

Presentation slides

  • Keep slides readable, visually consistent, and focused on one point at a time.
  • Include descriptive statistics and ggplot2 visualizations that directly support the story.
  • Other visual aids are welcome when they improve understanding.
  • Cite data sources and external material consistently.

Reproducible R script

  • Organize the script with section headers and explanatory comments.
  • Include every import, transformation, summary, and visualization needed to reproduce the presentation.
  • Explain techniques not covered in class.
  • Make sure the script runs from beginning to end without errors.

Submission instructions and presentation dates will be posted in Brightspace for each section.

Evaluation rubric

Dimension Evidence of strong work
Data transformation and descriptive statistics Accurate, purposeful preparation and summaries that support the question
Data visualization Clear, honest, well-labeled charts that reveal meaningful comparisons or trends
Data storytelling A focused narrative that connects context, evidence, meaning, and takeaway
Slides and visual materials Readable, polished, consistent, and appropriate for the audience
Group presentation Coordinated delivery, balanced participation, clear explanations, and effective Q&A
Code quality Reproducible, organized, documented, and error-free R code

Practical advice

  • You do not need to analyze every available variable.
  • Begin broadly, then narrow the analysis to the evidence that strengthens the story.
  • Treat exploration as iterative: summarize, visualize, question, refine, and verify.
  • Prefer a few well-explained findings over many disconnected charts.
  • Ask for help early when your ideal data structure or transformation path is unclear.

Collaboration and peer evaluation

  • Address collaboration concerns early and communicate them to the instructor while there is time to resolve them.
  • Each student will evaluate other groups’ presentations using the provided peer-evaluation form.
  • Brightspace will contain the submission procedure and grading details.

Browse Group Project Topics

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