Webinars

18M+ open datasets exist today, and growth is accelerating. But these data sets live in data portals without common taxonomies or architectures, and must first be cleaned and prepared by data users. Human and computers normalize, extract meaning, and identify correlations, but this work is siloed: used for one project, then lost forever, only to be repeated from scratch by the next person to touch the data. Open data can help us rise to humanity’s toughest challenges, but only if we maximize its network effect. To build the web of Linked Data, we have to start by connecting the people who are working with data. Visit: https://data.world/

In 2014 Committee of Presidents of Statistical Societies (COPSS) published a book entitled "Past, Present, and Future of Statistical Science" that contains 52 short chapters contributed by past winners of one of the COPSS Awards. The goal of the book (which is freely downloadable from the COPSS website or http://tinyurl.com/copss-ppf) was to "showcase the breadth and vibrancy of statistics, to describe current challenges and new opportunities, to highlight the exciting future of statistical science, and to provide guidance for future generations of statisticians (page xvii)." In this webinar, I will describe how these chapters were integrated into a theoretical statistics course to help students see the big picture and potential for statistics.

As enrollment in introductory statistics courses across the country rises, more instructors for these courses are needed. Many statistics courses are now taught by Graduate Teaching Assistants (GTAs). Little is known, however, about the training needs of GTAs to foster active learning and promote conceptual understanding, critical recommendations of the GAISE guidelines to improve undergraduate learning in statistics. This talk will discuss changes to our lab activities to incorporate GAISE recommendations of teaching for conceptual understanding, foster active learning, and integrating real data. We will also discuss initial findings concerning the struggles GTAs have with connecting their theoretical knowledge to conceptual ideas concerning confidence intervals for one population proportion. The material is based on work supported by NSF DUE 1504587.

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 http://moderndive.com 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: http://bit.ly/moderndive-causeweb

We present actual data gathered from a café run by business students. We give examples of time series forecasting and data mining applications, and frame problems as managerial questions to emphasize data-driven decision making.

In this webinar we will present our experiences and provide tips on how to implement a flipped classroom approach we call "Just-in-Time Teaching." In this method in and out of classroom activities are reversed; student preparation before class includes watching a brief lecture via video and responding to web-based discussion questions designed to elicit common misunderstandings students have, and class time is reserved for guided practice to reinforce new knowledge.

Our university recently began offering a bachelor’s degree in data science. One of the required courses for this major is a course on data summary and visualization. Fall Semester 2016 was the second time this course was offered at our university. In this talk, I will describe the content, structure, and pace of this course and provide examples of student output.

This webinar will provide a tour of CAUSEweb.org and its special collections and features. The webinar will also provide ways for community involvement in building the collections and seek audience suggestions for future projects.

Research on faculty professional development suggests that in order for faculty to change their teaching, they must perceive a problem, be presented with changes they can adapt to their own teaching style, and see evidence of change in student learning based on the changes. Many words in statistics pose a barrier for entry level students because they everyday meanings which differ from their discipline usage within statistics; this can lead to lexical ambiguity for students. The webinar will focus on two High-Impact, Little-Time (HILT) activities developed by faculty involved in a faculty learning community to help exploit lexical ambiguities associated with parameter. We will present the activities, along with the data that show the effectiveness of the activities with respect to student learning.

Professional development for educators can be done in a flexible format that meets the needs of teachers of statistics in a variety of contexts. Design principles and sample learning opportunities will be shared that are part of the Teaching Statistics Through Data Investigations MOOC for Educators. The course is offered several times a year and thus far has served over 2500 educators from all 50 states, and over 45 countries. See http://friday.institute/tsdi.