Using Visuals to Enhance Scientific Presentations

Choosing the right chart is half the battle in data storytelling. This one visual helped me go from “𝐖𝐡𝐢𝐜𝐡 𝐜𝐡𝐚𝐫𝐭 𝐝𝐨 𝐈 𝐮𝐬𝐞?” → “𝐆𝐨𝐭 𝐢𝐭 𝐢𝐧 10 𝐬𝐞𝐜𝐨𝐧𝐝𝐬.”👇 𝐇𝐞𝐫𝐞’𝐬 𝐚 𝐪𝐮𝐢𝐜𝐤 𝐛𝐫𝐞𝐚𝐤𝐝𝐨𝐰𝐧 𝐨𝐟 𝐡𝐨𝐰 𝐭𝐨 𝐜𝐡𝐨𝐨𝐬𝐞 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐜𝐡𝐚𝐫𝐭 𝐛𝐚𝐬𝐞𝐝 𝐨𝐧 𝐲𝐨𝐮𝐫 𝐝𝐚𝐭𝐚: 🔹 𝐂𝐨𝐦𝐩𝐚𝐫𝐢𝐬𝐨𝐧? • Few categories → Bar Chart • Over time → Line Chart • Multivariate → Spider Chart • Non-cyclical → Vertical Bar Chart 🔹 𝐑𝐞𝐥𝐚𝐭𝐢𝐨𝐧𝐬𝐡𝐢𝐩? • 2 variables → Scatterplot • 3+ variables → Bubble Chart 🔹 𝐃𝐢𝐬𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧? • Single variable → Histogram • Many points → Line Histogram • 2 variables → Violin Plot 🔹 𝐂𝐨𝐦𝐩𝐨𝐬𝐢𝐭𝐢𝐨𝐧? • Show part of a total → Pie Chart / Tree Map • Over time → Stacked Bar / Area Chart • Add/Subtract → Waterfall Chart 𝐐𝐮𝐢𝐜𝐤 𝐓𝐢𝐩𝐬: • Don’t overload charts; less is more. • Always label axes clearly. • Use color intentionally, not decoratively. • 𝐀𝐬𝐤: What insight should this chart unlock in 5 seconds or less? 𝐑𝐞𝐦𝐞𝐦𝐛𝐞𝐫: • Charts don’t just show data, they tell a story • In storytelling, clarity beats complexity • Don’t aim to impress with fancy visuals, aim to express the insight simply, that’s where the real impact is 💡 ♻️ Save it for later or share it with someone who might find it helpful! 𝐏.𝐒. I share job search tips and insights on data analytics & data science in my free newsletter. Join 14,000+ readers here → https://lnkd.in/dUfe4Ac6

I used to think colorful charts helped display information. Now I know they do exactly the opposite. When it comes to data visualization, color *is* crucial. But not in the way you’ve likely been taught. The general rule of thumb is that you should use color sparingly and strategically. In other words, never use color for the sake of being color*ful*. Here’s how: First, identify your core colors (I recommend 1-2 max): Option 1 ↳ Use your company’s (or client’s) brand colors. This is often the easiest and best choice. (But remember, you don’t have to use *all* the brand colors.) Option 2 ↳ Use an online color palette (check out the resources linked in the comments to get started). I’ve also searched Pinterest for things like “blue and green color palettes.” Second, follow best practices: Use grey as your default.  ↳ Create all your charts in greyscale first. Then, incorporate color to draw your audience’s eyes to the most important takeaways or data points. Use 1-2 core colors throughout your presentation.  ↳ Use your core colors to highlight the specific trends, categories, or insights you want your audience to pay attention to. Be aware of cultural associations.  ↳ Color symbolism varies across the globe - for example, red often carries a negative connotation in Western cultures, but represents luck and prosperity in Eastern/Asian cultures. Be mindful of color blindness.  ↳ Approximately 8% of men and 0.5% of women are colorblind (red-green being the most common). In general, less is more. Imagine someone were to look at your chart and say “Why is THAT particular bar blue? Why is THAT one green?” If you can’t give a clear answer, it's time to go back to the drawing board. —-— 👋🏼 I’m Morgan. I share my favorite data viz and data storytelling tips to help other analysts (and academics) better communicate their work.

Good research deserves good poster design. Here’s how to structure every section of your academic research poster They’ll teach you how to collect data. But no one teaches you how to present it. Here’s what academic research poster should include ——————————————— 𝗧𝗜𝗧𝗟𝗘 𝗢𝗙 𝗬𝗢𝗨𝗥 𝗥𝗘𝗦𝗘𝗔𝗥𝗖𝗛 → 1–2 lines only. → Make it specific, bold, and readable from 3 feet away. → Add your name(s), affiliations, and contact info (email or QR code to full paper). ——————————————— 𝗜𝗡𝗧𝗥𝗢𝗗𝗨𝗖𝗧𝗜𝗢𝗡 → 2–3 sentences on why this study matters → Use bullet points for major facts (e.g. disease burden, knowledge gap) → Optional: add one icon or small visual (e.g. world map if global) ——————————————— 𝗢𝗕𝗝𝗘𝗖𝗧𝗜𝗩𝗘𝗦 → Numbered list of research questions or hypotheses → Keep them short, clear, and preferably bolded ——————————————— 𝗠𝗘𝗧𝗛𝗢𝗗𝗢𝗟𝗢𝗚𝗬 → Study design (e.g. RCT, cohort, case-control) → Setting (country, site, year) → Sample population (eligibility, key demographics) → Variables (exposures, outcomes, confounders) → Data sources/tools (e.g. surveys, registries, labs) → Analysis plan (stats methods, software used) → Optional: one flowchart or timeline visual ——————————————— 𝗥𝗘𝗦𝗨𝗟𝗧𝗦 → Table: Key characteristics (age, sex, baseline traits) → Graph 1: Your main outcome → bar, line, or forest plot → Text Summary: 3–4 numbered findings with clear metrics (p-values, CIs, effect sizes) → Visuals: Maps for geographical data; survival curves if time-to-event is critical → Label everything: axes, legends, and font readable from 3 feet away ——————————————— 𝗗𝗜𝗦𝗖𝗨𝗦𝗦𝗜𝗢𝗡 → 2–3 bullet points interpreting the results → 1 bullet: main limitation → 1 bullet: key implication or recommendation ——————————————— 𝗖𝗢𝗡𝗖𝗟𝗨𝗦𝗜𝗢𝗡 → One sentence only → No new data; just your biggest takeaway or impact summary ——————————————— 𝗥𝗘𝗙𝗘𝗥𝗘𝗡𝗖𝗘𝗦 & 𝗔𝗖𝗞𝗡𝗢𝗪𝗟𝗘𝗗𝗚𝗠𝗘𝗡𝗧𝗦 → 2–3 most relevant citations → Funding sources and disclosure (if required) → Keep font tiny but readable up close ——————————————— If they have to squint, it’s not a poster; it’s a paragraph. Design it for clarity, not complexity. ♻️ Repost this to help a student, colleague, or conference team build better science communication. #AcademicPoster #ResearchDesign

Want to create better dataviz? Before you call your next data visualization complete, make sure its passes these three tests: 1. The Spartan Test: Strip it down. Ruthlessly assess every element in your chart. If removing something doesn’t change the message, it’s clutter. Clear visuals build trust — give your audience only what they need. 2. The Peek Test: Look away for 5 seconds, then glance back at your visual. Where does your eye go first? Chances are, that’s where your audience will focus too. Adjust until attention is drawn to the key insight. 3. The Colleague Test: Think it’s perfect? Share it with a colleague who hasn’t seen the analysis. Provide minimal context and give them 10-15 seconds to interpret. Ask what they take away — does it match your intent? Nail these three, and your data visualization will not just look good — it will communicate clearly and effectively. Three passing grades means it's ready to be presented. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

Do you want your data to make a difference? Transform your numbers into narratives that drive action—follow these five key steps: 📌 STEP 1: understand the context Before creating any visual, ask: - Who is your audience? - What do they need to know? - How will they use this information? Getting the context right ensures your message resonates. 📊 STEP 2: choose an appropriate graph Different visuals serve different purposes: - Want to compare values? Try a bar chart. - Showing trends? Use a line graph. - Need part-to-whole context? A stacked bar may work. Pick the right tool for the job! 🧹 STEP 3: declutter your graphs & slides More isn’t better. Remove unnecessary elements (gridlines, redundant labels, clutter) to let your data breathe. Less distraction = clearer communication. 🎯 STEP 4: focus attention Not all elements on your graphs and slides are equal. Use: ✔️ Color ✔️ Annotations ✔️ Positioning …to guide your audience’s eyes to what matters most. Help them know where to look and what to see. 📖 STEP 5: tell a story Numbers alone don’t inspire action—stories do. Structure your communication like a narrative: 1️⃣ Set the scene 2️⃣ Introduce the conflict (tension) 3️⃣ Lead to resolution (insight or action) Make it memorable! THAT'S the *storytelling with data* process! ✨ Following these five steps will help you create clear, compelling data stories. What's your favorite tip or strategy for great graphs and powerful presentations? Let us know in the comments!

Why showing text and graphics simultaneously is like trying to watch two movies at once - and the better alternative backed by research. Your brain has limits. Let's use them wisely. Most eLearning overloads learners with: ↳ Dense text blocks ↳ Complex graphics ↳ Information overload Here's the science-backed solution: 1️⃣ Split Processing Power • Your brain has two channels • Visual for graphics/images • Auditory for spoken words • Don't max out either one 2️⃣ The Power of Voice • Narration > on-screen text • Frees up visual processing • Reduces cognitive strain • Better retention rates 3️⃣ Strategic Implementation • Use audio for explanations • Keep visuals clean and focused • Sync narration with graphics • Let each channel do its job Real-world application: ☑️ Replace text walls with narration ☑️ Sync audio/visual timing perfectly ☑️ Save text for key terms only ☑️ Design for dual-channel processing The results? ↳ Reduced cognitive load ↳ Improved engagement ↳ Faster learning curves The secret isn't more content. It's smarter delivery. Your learners' brains will thank you. What small change could you make in your next course to ease your learners’ cognitive load?

The most compelling research presentation I gave broke every academic convention. Most research talks follow a tired script: Intro → Methods → Results → Conclusion. But that order buries your message. After giving hundreds of talks, I’ve found that the best ones flip the script—and put the audience first. Here are 3 changes I made that had the room buzzing: 1️⃣ Start with your conclusion. Open with your core message. Now, instead of wondering WHAT you found, your audience tracks HOW you got there. This shift keeps them engaged—and mirrors how we read papers. 2️⃣ Use figures > tables. Tables are fine in manuscripts. But in presentations, they overwhelm. A clean figure tells the story faster—and sticks longer. 3️⃣ Own the room. Don’t pace it. Pick three people—left, center, right. Speak to them in turn. Stay planted. Let your ideas move, not your feet. And just as important—3 things to avoid: 1️⃣ Don’t read your slides. You’re there to connect, not recite. Use keywords, not scripts. Practice until you can speak naturally—even without presenter notes. 2️⃣ Don’t overload with text. Your slide is not a manuscript. Stick to 5–6 short phrases max. Skip the periods to avoid the urge for full sentences. 3️⃣ Don’t show giant tables or figures If you have to say “I know you can’t read this,” cut it. Trim big tables/figures or split them into 2–3 slides. You don’t need flashy animations or fancy tools. Just clarity, structure, and presence. What’s one small change you’ll make in your next research talk to better serve your audience? ----- P.S. Join the Research Boost waitlist for early access to the tool—and behind-the-scenes lessons HERE: https://researchboost.com/ BONUS: When you subscribe, you instantly unlock my Manuscript Outline Blueprint. Please reshare 🔄 if you think this will be helpful to others…

I was sitting in a meeting, and a graph popped up during the presentation. It had five different colors, two types of chart elements (bars and lines), and it told multiple stories. I didn’t know where to look. My eyes – and brain – eventually gave up. The five-second rule (not the one about dropping food on the ground!) came from user research, and it measures how effectively information is communicated to the audience within the first five seconds. Originally used for testing web pages, it is now a recommended guide for interactive visual images – like infographics, charts, etc. Before you insert a complex graph into a presentation, I beg you to step away from your Excel file and consider the following: ☑ Can an audience understand this in five seconds? ☑ Is there a better way to tell this in a narrative? ☑ Is the chart necessary? If so, how can it be simplified? Does it have a clear title? Easy elements to understand? Remember, the more data points you have in a visual, the harder it is for your audience to know where to focus. And, if they are trying to figure out an image, they aren’t listening to you! Also, you have the curse of knowledge. You’ve been staring at this data for longer than five seconds. You are assuming your audience will know more than they do! Data is only helpful IF your audience can understand it; otherwise, it’s a reason for them to tune out! What are your tricks for simplifying complex information in presentations? I break charts into one or two slides, and I tell a story with them. Your audience needs to know why this chart matters to them! (I also avoid all the fancy options like 3D and breaking up pie charts! Simplicity for the win!) #CommunicationTips Image credit: visme dot com

Imagine you've performed an in-depth analysis and uncovered an incredible insight. You’re now excited to share your findings with an influential group of stakeholders. You’ve been meticulous, eliminating biases, double-checking your logic, and ensuring your conclusions are sound. But even with all this diligence, there’s one common pitfall that could diminish the impact of your insights: information overload. In our excitement, we sometimes flood stakeholders with excessive details, dense reports, cluttered dashboards, and long presentations filled with too much information. The result is confusion, disengagement, and inaction. Insights are not our children, we don’t have to love them equally. To truly drive action, we must isolate and emphasize the insights that matter most—those that directly address the problem statement and have the highest impact. Here’s how to present insights effectively to ensure clarity, engagement, and action: ✅ Start with the Problem – Frame your insights around the problem statement. If stakeholders don’t see the relevance, they won’t care about the data. ✅ Prioritize Key Insights – Not all insights are created equal. Share only the most impactful findings that directly influence decision-making. ✅ Tell a Story, Not Just Show Data– Structure your presentation as a narrative: What was the challenge? What did the data reveal? What should be done next? A well-crafted story is more memorable than a raw data dump. ✅ Use Clean, Intuitive Visuals – Data-heavy slides and cluttered dashboards overwhelm stakeholders. Use simple, insightful charts that highlight key takeaways at a glance. ✅ Make Your Recommendations Clear– Insights without action are meaningless. End with specific, actionable recommendations to guide decision-making. ✅ Encourage Dialogue, Not Just Presentation – Effective communication is a two-way street. Invite questions and discussions to ensure buy-in from stakeholders. ✅ Less is More– Sometimes, one well-presented insight can be more powerful than ten slides of analysis. Keep it concise, impactful, and decision-focused. Before presenting, ask yourself: Am I providing clarity or creating confusion? The best insights don’t just inform—they inspire action. What strategies do you use to make your insights more actionable? Let’s discuss! P.S: I've shared a dashboard I reviewed recently, and thought it was overloaded and not actionably created

People's brains can only do one thing at a time. In live presentations, text-filled slides will lead the audience to stop listening and start reading the slide. Their brains can either read, or they can listen. When you think about what goes on your slides, think about elements that are communicated much better visually. Graphs, charts, pictures are all examples of visuals that communicate information much more efficiently and effectively than can usually be done in words. But, a written version of your talk track is not a great use of slide space - remove that from the slide and speak to it instead. It makes for a cleaner slide and makes the audience dependent on the speaker for the "so what" or the significance of the slide. So for your next presentation, think about slides with fewer words, more visuals, and a verbal presentation that adds further context and explanation to what the audience sees on the slide.