Presented by: Chester Ismay and Albert Y. Kim
Abstract:
This webinar will provide a guide to creating a user-adaptable electronic textbook incorporating data visualization, data science, and other relevant pedagogical concepts into your introductory statistics course. We present our own introductory statistics and data science textbook available at that:
Focuses on the entirety of the data/science pipeline from importing data to visualizing and summarizing data to inferential techniques and developing students as effective data storytellers
Blurs the line between lecture and lab
Uses freely available modern, rich, and complex data sources
Leverages resampling and simulation to build statistical inference concepts
Most importantly, provides complete customizability to the instructor and reproducibility to the student
We’ll discuss how collaboration and crowd-sourcing have and will play a role in our textbook going forward and other open-source materials we are creating to better support introductory statistics/data science students learning the skills and tools that statisticians/data scientists are using today.
For the complete powerpoint presentation of today's webinar:
Aired: Tuesday, March 14th, 2017
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