Please join us for the next Journal of Statistics and Data Science Education webinar Tuesday, February 23rd at 4:00 PM ET.
Title: Bayesian Methods and the Statistics and Data Science Curriculum
Presenters: Jingchen (Monika) Hu (Vassar College), Kevin Ross (Cal Poly - San Luis Obispo), & Colin Rundel (University of Edinburgh/Duke)
Date and Time: Tuesday, Feb 23, 2021 04:00 PM Eastern Time (US and Canada)
Abstract:
The Journal of Statistics and Data Science Education recently published a cluster of papers on Bayesian methods (https://www.tandfonline.com/toc/ujse20/28/3?nav=tocList<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.tandf…>). The Bayesian cluster includes a presentation of how and why Bayesian ideas should be added to the curriculum; guidance on how to structure a semester-long Bayesian course for undergraduates; a discussion of the ever-evolving nature of Bayesian computing; a book review; and a panel interview of several Bayesian educators. For the February CAUSE/JSDSE webinar series, we’ve invited several authors of these provocative and informative articles to describe their work and its implications for statistics and data science education.
Jingchen (Monika) Hu is an Assistant Professor of Mathematics and Statistics at Vassar College. She teaches an undergraduate-level Bayesian Statistics course at Vassar, which is shared online across several liberal arts colleges. Her research focuses on dealing with data privacy issues by releasing synthetic data.
Kevin Ross is an Associate Professor of Statistics at Cal Poly San Luis Obispo. His research interests include probability, stochastic processes and applications as well as probability and statistics education.
Colin Rundel is a lecturer at the University of Edinburgh and an assistant professor of the practice in Statistical Science at Duke University. His research interests include applied spatial statistics with an emphasis on Bayesian statistics and computational methods.
Registration link: https://psu.zoom.us/webinar/register/WN_36pR2co_QYqtuyMi-VboFQ
Please join us for the next Journal of Statistics and Data Science Education webinar Tuesday, February 23th at 4:00PM ET.
Title: Bayesian Methods and the Statistics and Data Science Curriculum
Presenters: Jingchen (Monika) Hu (Vassar College), Kevin Ross (Cal Poly - San Luis Obispo), & Colin Rundel (University of Edinburgh/Duke)
Date and Time: Tuesday, Feb 23, 2021 04:00 PM Eastern Time (US and Canada)
Abstract:
The Journal of Statistics and Data Science Education recently published a cluster of papers on Bayesian methods (https://www.tandfonline.com/toc/ujse20/28/3?nav=tocList<https://nam10.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.tandf…>). The Bayesian cluster includes a presentation of how and why Bayesian ideas should be added to the curriculum; guidance on how to structure a semester-long Bayesian course for undergraduates; a discussion of the ever-evolving nature of Bayesian computing; a book review; and a panel interview of several Bayesian educators. For the February CAUSE/JSDSE webinar series, we’ve invited several authors of these provocative and informative articles to describe their work and its implications for statistics and data science education.
Jingchen (Monika) Hu is an Assistant Professor of Mathematics and Statistics at Vassar College. She teaches an undergraduate-level Bayesian Statistics course at Vassar, which is shared online across several liberal arts colleges. Her research focuses on dealing with data privacy issues by releasing synthetic data.
Kevin Ross is an Associate Professor of Statistics at Cal Poly San Luis Obispo. His research interests include probability, stochastic processes and applications as well as probability and statistics education.
Colin Rundel is a lecturer at the University of Edinburgh and an assistant professor of the practice in Statistical Science at Duke University. His research interests include applied spatial statistics with an emphasis on Bayesian statistics and computational methods.
Registration link: https://psu.zoom.us/webinar/register/WN_36pR2co_QYqtuyMi-VboFQ
The Consortium for the Advancement of Undergraduate Statistics Education is happy to announce our 57th Cartoon Caption Contest – now ongoing every month for nearly four years! Each month a cartoon, drawn by British cartoonist John Landers, is posted for you and your students to suggest statistical captions (cartoons are posted at the beginning of the month and submissions are due at the end of the month). The caption contest is offered as a fun way to get your students thinking independently about statistical concepts.
The next cartoon and the entry rules for the contest ending February 28 are at
https://www.causeweb.org/cause/caption-contest/february/2021/submissions
The best captions will be posted on CAUSEweb and the winner(s) will receive their choice of a coffee mug or t-shirt imprinted with the cartoon and their caption.
Enjoy.
December Results: There were 25 entries for the October caption contest that featured a cartoon showing a sports stadium where the ground cover was being installed. But half of the installation being rolled out was for a football field and the other half was for a tennis court. The winning caption for the December contest was “split-plot designs are important in the field,” written by Larry Lesser from The University of Texas at El Paso. Larry’s caption can be used to discuss designs when one factor is harder to vary than others (and the root of the term “split-plot design” in agriculture). An honorable mention this month goes to John McSweeny, a student at Penn State University for his caption “Well, the sample had Football and Tennis tied for most the popular sport so here you go,” that would aid in discussing how the results of surveys are used. A second honorable mention goes to an anonymous submitter for their caption: "Errors in merging data can really have a negative impact on reporting the score!," which can be used in a data science-oriented class discussing merging different data sets.
January Results: There were 32 entries for the January caption contest that featured a cartoon showing an optometrist’s office with a patient reading an eye chart. Instead of letters, the eye chart has numbers and statistical graphics. The winning caption for the January contest was “Not focusing on graphical data displays is somewhat short sighted,” written by Charlie Smith from North Carolina State University. Charlie’s caption can be used to discuss the importance of graphical displays in drawing meaning from data. An honorable mention this month goes to Sara Letardi from LSTAT for her caption “With your glasses you can see the world, but with statistics you can understand it,” that would aid in discussing how statistics provides a paradigm for understanding the world through data. A second honorable mention goes to Rowan Collier, a student at Kenston High School for his caption: "Understanding misleading graphs doesn’t require 20/20 vision!," which can be used in a discussion of critiquing possible bias in graphical displays
Thanks to everyone who submitted a caption and congratulations to our winners!
Please join the Teaching and Learning webinar Tuesday, February 9th at 2:00.
Title: Teacher Education Curriculum Materials that Develop Statistical Knowledge for Teaching
Presenters: Stephanie Casey, Andrew Ross (Eastern Michigan University)
Date and Time: Tuesday, February 9, 2021 - 2:00pm
Abstract: Statistics is more important than ever in today's data-driven world. This is reflected in the increased level of statistics understanding expected of K-12 students according to the CCSS-M and state-level standards. To develop middle and high school teachers' statistical knowledge for teaching, the MODULE(S^2) project has created curriculum materials for use in introductory statistics course(s) that preservice secondary teachers take. The materials develop preservice teachers’ subject matter and pedagogical content knowledge for teaching statistics as well as their equity literacy. In this webinar, we will provide an introduction to these materials including examples of statistical tasks and classroom videos from the materials. Alignment of these materials with ASA’s GAISE, ASA’s Statistical Education of Teachers report, and the Association of Mathematics Teacher Educator's Standards for Preparing Teachers of Mathematics will be highlighted. Also, we are recruiting faculty to be piloters for the materials. To find sample materials, visit https://modules2.com/statistics/, and to indicate you are interested in piloting, please fill out the form at https://modules2.com/use-our-materials/.
Registration link: https://psu.zoom.us/webinar/register/WN_FnTiWsSKR8KIibskosuipA