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All Statistics DataChats

R STATISTICS

James Curley, 4 December 2017

James is an Associate Professor in the Department of Psychology at University of Texas Austin in the Behavioral Neuroscience division. He received a Ph.D. from Cambridge University in 2003 and completed post-doctoral research at Cambridge University and Columbia University before becoming an Assistant Professor of Psychology at Columbia University in 2012. Dr. Curley’s current research interests are in studying the social dynamics of animals. Dr. Curley teaches several undergraduate and graduate courses, including R programming for Behavioral Scientists and Statistics & Research Design.

R STATISTICS

Zev Ross, 6 November 2017

Zev is the President of ZevRoss Spatial Analysis, a company that focuses on data science, machine learning, and development of data applications with a focus on spatial data. He is the author or co-author of over 40 peer-reviewed publications that focus on public health, spatial analysis and statistics. Zev also runs a popular data science blog and teaches workshops on spatial analysis and machine learning with R.

R STATISTICS

Charlotte Wickham, 19 October 2017

Charlotte is an Assistant Professor in the Department of Statistics at Oregon State University and an avid R programmer with a passion for teaching.

R STATISTICS

David Robinson, 3 October 2017

Dave is a Data Scientist at Stack Overflow and well known for his blog Variance Explained.

PYTHON STATISTICS

Justin Bois, 14 August 2017

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.

R STATISTICS

Rob Hyndman, 4 May 2017

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.

R STATISTICS

Arnaud Amsellem, 28 April 2017

Arnaud has over 20 years of experience as a quantitative trader. He is creator and author of the R Trader blog (www.thertrader.com).

R STATISTICS

Barry Rowlingson, 28 March 2017

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.

R STATISTICS

Ben Baumer, 19 December 2016

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.

R STATISTICS

Mine Çetinkaya-Rundel, 17 December 2016

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.

R STATISTICS

Jo Hardin, 13 December 2016

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.

R STATISTICS

David Stoffer, 12 December 2016

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.

R STATISTICS

David Robinson, 3 December 2016

Dave is a Data Scientist at Stack Overflow and well known for his blog Variance Explained. He talks about his passion for blogging, the importance of building a data science portfolio, why you should learn SQL and much more.

R STATISTICS

Charlotte Wickham, 1 November 2016

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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