We all know how to specify a table and our processes support this. However, designing an awesome data visualization does not work this way. Our approach to table specification does not work?
In this second episode. I talk about how you can create a great visualization.
Here are the following important tips I’m speaking about:
- Importance of details
- Co-creation with the audience
- KOL engagment
- Multiple review rounds
- Testing and refinement
- Start with pen and paper
- Focus on the larger topics like which plot to use first and then fine-tune to a more detailed level taking care of
- Use of colour
- Title
- Labels, legends
- Alignment
- Footnotes
- Supporting text
- For dashboards set up
- Filter and sorting options
- Arrangement of multiple displays
- Highlighting options
- Hover over options
- Digging deeper options
- Encouraging and giving feedback
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This group was set up to help each other to become more effective statisticians. We’ll run challenges in this group, e.g. around writing abstracts for conferences or other projects. I’ll also post into this group further content.
I want to help the community of statisticians, data scientists, programmers and other quantitative scientists to be more influential, innovative, and effective. I believe that as a community we can help our research, our regulatory and payer systems, and ultimately physicians and patients take better decisions based on better evidence.
I work to achieve a future in which everyone can access the right evidence in the right format at the right time to make sound decisions.
When my kids are sick, I want to have good evidence to discuss with the physician about the different therapy choices.
When my mother is sick, I want her to understand the evidence and being able to understand it.
When I get sick, I want to find evidence that I can trust and that helps me to have meaningful discussions with my healthcare professionals.
I want to live in a world, where the media reports correctly about medical evidence and in which society distinguishes between fake evidence and real evidence.
Let’s work together to achieve this.
