Advice I always seem to give to students in their presentations.

1. If you have multiple figures on a slide, animate them, and introduce them 1 at a time.

2. Be really careful with tables. Highlight important information. Don't expect everyone to just "get it".

3. Manage cognitive load. Usually, the people watching your presentation are tired and cranky. Feed them information accordingly.

4. Use visuals that resonate with your audience. Do your research about this.

5. If you want someone to draw a conclusion for something, use it as a title.

6. Use color sparingly to highlight important data in a chart.

7. Do not show model output straight out of R. Do the work of filtering and showing the most important results.

8. Be willing to take feedback. Actually, ask for specific feedback with the attitude of making your work better.

I should probably go up to 10, but those are the ones I can think of right now.

Just adding these to the main thread:

9. Ask yourself what the essential figures are. Strip everything out that doesn't lead to those figures. Save the other stuff as backup slides.

10. Figure out the story of your talk and use it to make decisions about what to leave out.

If you want to learn more about this topic, you can check out my “Data Storytelling” presentation here:

https://laderast.github.io/data_storytelling_talk/#1

There is a lot of cognitive science about effective figures and presentations, and you should use evidence-based methods to present.

At the heart of all of this is empathy for your audience.

If you don't care about your audience, why should they care about you and your work?

An excellent real world example is the #rstudioglobal keynote by @jburnmurdoch about visualizing the pandemic and the process of improving the visualizations given public feedback. Highly recommended! https://rstudio.com/resources/rstudioglobal-2021/reporting-on-and-visualising-the-pandemic/