---
title: "Final Project Presentation"
subtitle: "Data Quality Assurance + Visualization"
date: last-modified
---

PSYC 859 Spring 2026

## Due date

- In-class presentation: Thursday, 4/23/2026 (Week 14)
- Upload slides/handout to Canvas by the time listed there so they can be compiled for class

## Presentation format

- Length: 15 minutes, plus 1-2 minutes of questions
- Format: slides (PowerPoint, Keynote, PDF) or a one-page handout

## Presentation guidelines

In your presentation, briefly walk the class through the data quality assurance and visualization project you developed over the semester. The goal is to communicate the dataset, the workflow you built, and the clearest substantive or methodological insight that emerged from your analysis.

A strong presentation will usually include the following pieces:

1. **Conceptual overview** (approximately 2 minutes)
   - What is the motivating question, problem, or story?
   - Why is this project substantively interesting?
   - Who is the intended audience for the final figure(s) or analysis?

2. **Data overview** (approximately 2 minutes)
   - What do the data represent?
   - What is the unit of analysis?
   - What is the general structure of the dataset?
   - When useful, describe the data using standard terminology such as categorical, ordinal, continuous, repeated-measures, time series, or longitudinal data.

3. **Workflow + QA highlights** (approximately 2 minutes)
   - What were the main challenges in preparing the data for visualization and analysis?
   - Highlight 1-2 important preprocessing, validation, or QA decisions.
   - Briefly explain how you documented those decisions in your workflow.

4. **EDA overview** (approximately 2-3 minutes)
   - Show one or two exploratory plots that helped you understand the data or identify data-quality issues.
   - These do not need to be publication-ready. Their purpose is to show how visualization informed your thinking, debugging, or quality-assurance process.

5. **Formal figure presentation** (approximately 5 minutes)
   - Present your strongest polished figure or set of figures.
   - Clearly state the intended takeaway.
   - When possible, follow the presentation recommendations discussed in class, including Bertin's three stages of reading, font legibility, and effective visual highlighting (for example, using a pointer, callouts, or highlighted regions) to direct attention to the most important parts of the figure.
   - If possible, use a figure that shows relationships among more than two variables, multiple levels of a data hierarchy, or a meaningful comparison across groups, time, or conditions.
   - If your clearest story is best told with a simple figure, that is fine; in that case, consider showing two complementary plots rather than stretching one simple plot over the full presentation segment.

6. **Wrap-up** (approximately 1 minute)
   - What did you learn from the project?
   - What would you do next if you had more time?

## Tips for a strong presentation

- Prioritize legibility: make sure text, axes, legends, and annotations are readable from the back of the room.
- Use concise verbal framing and on-figure annotation to direct attention to the main pattern or conclusion.
- If a figure is complex, build it up gradually or zoom in on the part you want the audience to read.
- Practice the timing so you can move efficiently through the setup sections while leaving enough time to interpret your figures and state the main takeaway clearly.
