The Consortium for the Advancement of Undergraduate Statistics Education is happy to announce our 74th Cartoon Caption Contest! 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 July 31 are at
https://www.causeweb.org/cause/caption-contest/july/2022/submissions
The best submission will be posted on CAUSEweb and the winner(s) will receive their choice of a coffee mug or t-shirt imprinted with the final cartoon.
Enjoy.
[Engineering drawing Description automatically generated]
June Results:
The June caption contest cartoon is shown here. The judges found the winning caption to be “While Mike wrote furiously to describe important patterns in the data, Alicia calmly created a visualization to tell the story," written by Rob Carver from Stonehill College. Rob’s caption highlights how the right visualization can communicate complex patterns in data more easily than written descriptions. An honorable mention this month goes to Rosie Ching from Singapore Management University for her caption, “Not mastering the basics of time series may just cost you an arm and a leg,” which suggests a similar theme made specific to issues of trends over time.
Thanks to everyone who submitted a caption and congratulations to our winners!
Dear all,
Happy July! CAUSE Research is starting a reading group to read through the
articles mentioned in Rob Gould’s keynote talk at eCOTS 2022. BIG thanks to
those who participated in our first meeting a few weeks ago. Now, we are
writing to invite you to our second meeting on *July 20, 2022 at 2:00PM EST*
with the following article:
*Article: Erickson, T., Wilkerson, M., Finzer, W., & Reichsman, F. (2019).
Data moves. Technology Innovations in Statistics Education, 12(1).
http://dx.doi.org/10.5070/T5121038001
<http://dx.doi.org/10.5070/T5121038001> *
Please register in advance for this meeting:
https://ufl.zoom.us/meeting/register/tJAldO2oqT8oHNx0wT9TpTojpjT7HvV9q_LQ
After registering, you will receive a confirmation email containing
information about joining the meeting.
General Format of the reading group:
· We will meet for one hour to talk about the paper.
· You don’t have to attend each time to participate in the reading
group. Join us whenever you can!
· We will meet on the first and third Wednesdays during the summer.
The remaining three summer meetings are scheduled on *July 20*, *August 3*,
and *August 17*, all at *2:00pm EST*.
· Participants will discuss a time for the Fall semester.
· We will read through one paper every two weeks until December
2022.
· Participants that are interested will be host for an article from
the list of 14 papers.
· The host will curate a list of 4 to 5 questions to get the
conversation started from the article that they pick from the list of 14
articles.
· One possible outcome of the reading group may be to contribute to
a blog article for StatTLC
<https://urldefense.proofpoint.com/v2/url?u=https-3A__nam10.safelinks.protec…>
.
Look forward to seeing you soon!
Shu-Min Liao and Megan Mocko
This month, in the CAUSE (Consortium for the Advancement of Undergraduate Statistics Education) / JSDSE (Journal of Statistics and Data Science Education) webinar series, we highlight the research article, Integrating Data Science Ethics Into an Undergraduate Major. In the webinar, the presenters will present a programmatic approach to incorporating ethics into an undergraduate major in statistical and data sciences. They will discuss departmental-level initiatives designed to meet the National Academy of Sciences recommendation for integrating ethics into the curriculum from top-to-bottom as their majors progress from the introductory courses to the senior capstone course, as well as from side-to-side through co-curricular programming. They will also provide six examples of data science ethics modules used in five different courses at their liberal arts college, each focusing on a different ethical consideration. The modules are designed to be portable such that they can be flexibly incorporated into existing courses at different levels of instruction with minimal disruption to syllabi. The presenters will connect their efforts to a growing body of literature on the teaching of data science ethics, present assessments of their effectiveness, and conclude with next steps and final thoughts.
Article: https://www.tandfonline.com/doi/full/10.1080/26939169.2022.2038041
Presented By: Benjamin S. Baumer (Smith College) and Katherine M. Kinnaird (Smith College)
Benjamin S. Baumer<https://beanumber.github.io/www/> is an associate professor<https://www.smith.edu/academics/faculty/ben-baumer> in the Statistical & Data Sciences<https://www.smith.edu/academics/statistics> program at Smith College. Ben is a co-author of The Sabermetric Revolution<https://www.pennpress.org/>, Modern Data Science with R<http://mdsr-book.github.io/index.html>, and the second edition of Analyzing Baseball Data with R<https://www.routledge.com/Analyzing-Baseball-Data-with-R-Second-Edition/Mar…>. Ben has received the Waller Education Award<https://www.amstat.org/your-career/awards/waller-awards> from the ASA Section on Statistics and Data Science Education, the Significant Contributor Award<https://community.amstat.org/sis/aboutus/honorees> from the ASA Section on Statistics in Sports, and the Contemporary Baseball Analysis Award<http://sabr.org/latest/baumer-brudnicki-mcmurray-win-2016-sabr-analytics-co…> from the Society for American Baseball Research. His research interests include sports analytics, data science, statistics and data science education, statistical computing, and network science.
Katherine M. Kinnaird is the Clare Boothe Luce Assistant Professor of Computer Science and Statistical & Data Sciences at Smith College. She is a computational researcher working at the intersection of machine learning, mathematics and cultural analytics. Kinnaird has been involved with the Workshop for Women in Machine Learning (WIML), the American Mathematical Society's Committee on Education, and the Women in Music Information Retrieval (WiMIR) Workshop.
The webinar will take place on July 19th, from 1:30-2:00 pm EDT. Please note the earlier time .
Registration is required but is free:
https://www.causeweb.org/cause/webinar/jsdse/2022-07
We hope that you can join us for an informative discussion.
Sincerely,
Leigh Johnson (Capital University)
Moderator, CAUSE/JSDSE Webinar Series