Data Science—these days, we hear about it everywhere. And statisticians play a big role in this newly emerging field. Statisticians have always been involved with data—making sense of data, formulating ways to make decisions founded in data and evidence, devising the best ways to collect data. To handle the recent explosion of data, we statisticians have expanded our skill-set and our research approaches in order to extract information from huge and complex data sets. We are developing new statistical methods to make sense of data in more complex forms. We are also teaming up with computer scientists to increase the impact of our research and training. And our collaborations with researchers in areas such as health care, bioinformatics, and biodiversity not only solve real-world problems, but help us add to the tool set of data science methods.
Education and Training
The Statistics Department offers many avenues for training in Data Science. Our academic programs focus on statistics—both theory and applied data analysis, and emphasize skills in computing, collaboration, and communication. Our specialized courses include Introduction to Data Science (DSCI 100), Methods for Statistical Learning (STAT 406), and Exploratory Data Analysis (STAT 545), which trains in data wrangling and exploration and analysis with R. Our Applied Statistics and Data Science Group (ASDa) offers a variety of workshops, with particular expertise in training in R.
For those wanting an intensive 10-month program of study, we offer a Master of Data Science, in partnership with the Department of Computer Science.
All faculty members in the Statistics Department are involved in some component of what we call Data Science, since all faculty members are developing new statistical techniques to make sense of data. Professor Jenny Bryan is particularly noteworthy for her involvement in Bioinformatics and software engineering. Professor Alex Bouchard-Côté, with a PhD in Computer Science, is adept with computer intensive methods for analysis of complex data. Please browse our research areas to find out more.
New opportunities for research and industry collaborations abound, through initiatives related to the Cascadia Innovation Corridor, linking British Columbia, Washington, and Oregon. One focus is via the Cascadia Urban Analytics Cooperative, a joint initiative between Microsoft, the University of Washington, and the University of British Columbia.
Help with your Data Science Needs
Are you a UBC researcher with a challenging data set? A company or research unit that doesn't have in-house expertise? Find out how we can help you with your data.