<p>Let's welcome Ciera Martinez, data scientist, biologist, and co-organizer for the R-ladies SF, and Mathilde Chen, PhD Student, for our next meetup.</p> <p>Warning: please complete this form for registration (in addition to registration on meetup website):<br/><a href="https://docs.google.com/forms/d/e/1FAIpQLSdzRsFf8EMnWnznh4Od69KMZI-hgAFM3PdNqlOxUNFVtDP0Vw/viewform?usp=pp_url" class="linkified">https://docs.google.com/forms/d/e/1FAIpQLSdzRsFf8EMnWnznh4Od69KMZI-hgAFM3PdNqlOxUNFVtDP0Vw/viewform?usp=pp_url</a></p> <p>Unleashing the power of biodiversity data with R (Ciera):</p> <p>Biodiversity data can take many forms, from photographs of bird feathers from museums to 3D CT-scans of extinct animals. Natural History Museums and Botanical Gardens have been digitizing their collections for over ten years yielding billions of data points culminating in one of the most exciting data resources the world has to offer. Evolutionary Biologist, Ciera Martinez, will be speaking about biodiversity data and her work as a current Mozilla Science Fellow. Her and her team have been working at the Berkeley Institute of Data Science exploring what the world of biodiversity data has to offer. You learn more about this project at curiositydata.org. In addition to talking about her biodiversity data project, she will speak about data science in academia and will host a brief workshop on how to use R to map fossils of extinct animals.</p> <p>Survival analysis (Mathilde):</p> <p>Data where value of a measurement or of an observation is partially known is defined as censored data. This type of data is very common in biomedical sciences, social sciences, engineering and ecology and particular care is required in their analysis. To deal with such data, survival analysis can be used.</p> <p>One of the main purposes of survival analysis is to estimate survival functions, i.e. the expected duration of time until one or more events happen, and their dependence on explanatory variables. In this presentation, we will see the caracteristics of this collection of statistical methods and their implementation in R, through the survival R package. Let's do survival analyses without suffering!</p>