- Do you effectively communicate complex data?
- How can visualization help you when you aree
- analyzing data?
- reporting data?
- What initiatives and groups work on this topic and will help you?
In today’s episode, we talk about the advantages of using visualizations when analyzing and communicating data.
We also discuss the following points:
- How our organizations prioritize visualizations?
- What we love about visualizations?
- What are the principles of visualization statisticians should know about?
- How to create interesting, innovative, and purposeful visualizations?
Listen to this episode to learn more on visualizations and share this with others who might learn from it!
References:
- Visualization special interest group (VIS SIG)
- Wonderful Wednesday announcement and link to registration
- Google team BigPicture
- Google tutorial
- Datastori.es episode on visualization of uncertainty
- Github D3 gallery
- Novartis visualization initiative and cheat-sheet
- Stratos initiative
- data visualization society
- Fundamentals of Data Visualization – online book
- Data Visualization – A practical introduction – online book
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Mark Baillie
Advanced Methodology and Data Science, Clinical Development and Analytics. Novartis Pharma AG
Mark is a methodologist supporting the clinical development and analytics department at Novartis. He has a focus on data visualization working on a number of internal and external initiatives to improve the reporting of clinical trials and observational studies.
Rachel Phillips
Rachel Phillips was awarded a NIHR Doctoral Research Fellowship in 2018 to undertake her PhD at Imperial College London. Her research focuses on the reporting and analysis of adverse events in pharmacological RCTs and developing statistical methods to better identify adverse drug reactions. Prior to this, Rachel worked as a clinical trial statistician for 7 years in the UK and Singapore across a range of disease areas.
Join The Effective Statistician LinkedIn group
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.
