Big Ideas to Help Statistics Students Learn to "Think With Data"

This is an exciting time to be a statistician. The contribution of the discipline of statistics (the science of learning from data) to scientific knowledge is widely recognized, but there are challenges as well as opportunities in this new world of data.  In this talk, I will discuss a number of examples, questions, and big ideas with major implications for how we teach statistics and data science. In a world of found data, what issues of design and confounding are needed to disentangle complex relationships?  What theoretical foundations are needed for statisticians? Since statistics is increasingly a ‘team sport’, how do we teach students to work effectively in groups and communicate their results? And how do we integrate big data-related capacities into our curricula—early and often?  The analysis of the abundant data now available to us requires multi-variable thinking, an understanding of confounding, simulation-based problem solving, and other data-related skills.