Justin Bois is a lecturer in the Division of Biology and Biological Engineering at the California Institute of Technology. He teaches nine different classes there, nearly all of which heavily feature Python. He is dedicated to empowering students in the biological sciences with quantitative tools, particularly data analysis skills. Beyond biologists, he is thrilled to develop courses for DataCamp. In this DataChat, Hugo and Justin discuss different aspects of data science, including data science education, and Justin shares his advice to those getting started in the field.
Rob J. Hyndman is Professor of Statistics at Monash University, Australia, and Editor-in-Chief of the International Journal of Forecasting. Rob is the author of over 150 research papers and books in statistical science. In 2007, he received the Moran medal from the Australian Academy of Science for his contributions to statistical research, especially in the area of statistical forecasting. He is the author of about 20 R packages, including the popular forecast package.
Richie chats to Barry about tropical diseases, how he became a geographer, R tools for spatial statistics, R and QGIS, the trials of converting between different data structures, the spatial stellar cluster, interactive maps, and trends in spatials stats.
Ben is an Assistant Professor in the Statistical & Data Sciences Program at Smith College. He completed his Ph.D. in Mathematics at the Graduate Center of the City University of New York in 2012. He is an Accredited Professional Statistician™ by the American Statistical Association and was previously the Statistical Analyst for the Baseball Operations department of the New York Mets. Follow Ben here: https://twitter.com/BaumerBen Together with Nick, Ben talks about his path to becoming a sabermetrician, his passion for teaching, the importance of subject-matter expertise in data science and more.
Mine is the Director of Undergraduate Studies and an Associate Professor of the Practice in the Department of Statistical Science at Duke University. She received my Ph.D. in Statistics from the University of California, Los Angeles, and a B.S. in Actuarial Science from New York University’s Stern School of Business. Her work focuses on innovation in statistics pedagogy, with an emphasis on student-centered learning, computation, reproducible research, and open-source education. Find Mine's website here: http://www2.stat.duke.edu/~mc301/ Together with Nick, Mine talks about her path into becoming a Statistician, teaching R, trends in the broader data science community and much more.
Jo is a Professor of Mathematics at Pomona College with many years of R experience. She has a pure passion for education and has been working on the ASA’s undergraduate curriculum guidelines where she strongly advocated the infusion of data science into the undergraduate statistics curriculum. Together with Nick, Jo talks about R's place in the stats curriculum, the role of technology in education, what advice she would give to people just starting in statistics, bootstrapping, and much more.
David Stoffer is a Professor of Statistics at the University of Pittsburgh. He is member of the editorial board of the Journal of Time Series Analysis and Journal of Forecasting. David is the coauthor of the book "Time Series Analysis and Its Applications: With R Examples", which is the basis of his course. Another (free) book he wrote on Time Series Analysis is available here: http://www.stat.pitt.edu/stoffer/tsa4... Together with Lore, David talks about his path to Statistics, his teaching method, his latest book, how he got into R, and much more.
Charlotte is an Assistant Professor in the Department of Statistics at Oregon State University and an avid R programmer with a passion for teaching. She talks us through her first exposure to R, why a tool like GitHub is fantastic, and how to use your cat and a GPS tracker to collect data for your R coding experiments :-)
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