- Views 346
In this webinar, you will learn how to decide what type of graph to use based on the characteristics of your dataset and how to create effective dot plots, box plots, violin plots, and combinations of these plots. We will also take a look at the free tools available for creating more informative graphics and address common misconceptions and questions that people have when switching from bar graphs to more informative graphics.
What you’ll take away from the webinar:
- Why bar graphs of continuous data are potentially misleading and don’t allow others to critically evaluate the data
- Why dot plots are best for very small samples
- How to recognise informative graphs that allow others to critically evaluate the data
- Get an overview of free tools available to make more informative graphics
Tracey L. Weissgerber, webinar chair and member of the eLife Early-Career Advisory Group.
Tracey is an Assistant Professor and researcher in the Division of Nephrology and Hypertension, and a meta-researcher and visiting scientist at QUEST (Quality | Ethics | Open Science | Translation - Charité - Universitätsmedizin Berlin and the Berlin Institute of Health). She holds BSc, BPHE, MSc and PhD degrees from Queen’s University in Kingston (Canada). She completed a postdoc at Magee-Womens Research Institute in Pittsburgh before coming to Mayo Clinic as a BIRCWH Scholar (Building Interdisciplinary Research Careers in Women’s Health) in 2012. As a vascular physiologist, her research focuses on the mechanisms that link preeclampsia with an increased risk of cardiovascular disease later in life.
Dr. Weissgerber also conducts meta-research designed to improve the quality of data presentation and statistical analysis in basic science and creating tools to transform scientific papers from static reports into interactive datasets. Her collaborative team’s meta-research paper on bar graphs has been viewed more than 330,000 times and contributed to journal policy changes that ban bar graphs of continuous data and encourage authors to use more transparent figures that show the data distribution.
We welcome comments, questions and feedback. Please annotate publicly on the article or contact us at hello [at] elifesciences [dot] org.
Interested in our full selection of #ECRWednesday webinars, on topics such as preprints, finding funding and more? Take a look at the collection of past reports and recordings.