University of Minnesota
Here we will keep you informed, as well as, post materials and links from our meetings, seminars, and workshops. Happy computing.
The meetings will take place in EdSciB Room 10. [map] from 3:00pm–4:30pm
Join us afterward at the Kitty Cat Klub for a social hour and further conversation.Sept. 18 | Promoting Undergraduate Data Science with DataFest Rob Gould UCLA The world of Big Data has created new demands on undergraduate students of statistics. In addition to being able to 'think with data', they need improved computational thinking abilities so that they can compute with data. I will discuss DataFest, an undergraduate competition modeled after hackathons that celebrates data and encourages undergraduates to expand their skills, step out of their comfort zones, and tackle a real challenge – posed by a real company or government entity – involving rich, complex data. This is primarily a fun and friendly, though intense, competition that serves as a valuable stepping stone to students' future careers. For faculty, it provides a useful opportunity for evaluating our program at UCLA and establishing ties with local industry and research facilities. |
Oct. 16 | Data Management for the Social Sciences Alice Motes Social Science Data Curation Specialist and CLIR Postdoctoral Fellow, University of Minnesota Libraries Learn how to manage your data in a coherent, efficient, secure, and transparent way that complies with the University’s new Data Management Policy. The playing field for how we need to manage our research data has changed. We face increasingly complex research situations, emphasis on security and openness of data, and new requirements from journals, federal agencies, and the University. This session of Computing and Conversation led by Alice Motes, Social Science Data Curation Specialist at University of Minnesota Libraries, will present tools and techniques we can use to address these challenges [slides] | [video] |
Nov. 20 | Qual-Tricks: Superpower Your Survey A panel of experienced researchers will share how they have used Qualtics in innovative ways to understand and inform their survey results. The panel includes:
[slides - Tiffany] | [slides - Alex] | [video - part I] | [video - part II] |
The meetings will take place in EdSciB Room 10 [map] from 11:30am–12:30pm
Feb. 2 | How do I Make that Plot? The Grammar of a Graph |
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Feb. 16 | What is Wrong with My Model? Visual Diagnostics |
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Mar. 2 | Make your Plots Interactive: A Shiny Overview |
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Mar. 13 | Design-a-thon |
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Mar. 30 | What is a Bitmap? Getting your Graphics Ready for Publication |
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Apr. 13 | Where is that File? Organizing Folders and Files for Research Projects |
Feb 2 | Flexible, Beautiful, Customized Graphs Understanding ggplot2's grammar [HTML slides] | [PDF slides] | [R markdown] | [R script] |
Feb 16 | Eyeballing Your Models Using visual diagnostics to assess model fit [HTML slides] | [PDF slides] | [R markdown] | [R script] |
Mar 2 | Don't Start from Scratch Interacting with your graphics [PDF slides] | [R markdown] | [R script] |
Mar 30 | QME SEMINAR, 12:00–1:00pm: Teaching precursors to data science in introductory and second courses in statistics (Nick Horton, Amherst College) [slides and supplementary resources] |
Apr 13 | Stave off Chaos: Organizing your Research Project Panel discussion:
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Apr 27 | Eyes to the Horizon A preview of the QME package and an eye toward the future of education & computing [pdf slides] |
Apr. 27 | Topic TBD by Crowdsourcing |
Get it on your Google Calendar [click here]. Then click the "Add to Google Calendar" icon on the bottom-right of the screen.
Here are some other events that may be of interest.
Jan. 6 | Data Viz Meetup 11:00am–12:00pm; Walter Library 310 UL |
Feb. 3 | Data Viz Meetup 11:00am–12:00pm; Walter Library 310 UL |
Mar. 3 | Data Viz Meetup 11:00am–12:00pm; Walter Library 310 UL |
Apr. 7 | Data Viz Meetup 11:00am–12:00pm; Walter Library 310 UL |
May 5 | Data Viz Meetup 11:00am–12:00pm; Walter Library 310 UL |
Jun. 2 | Data Viz Meetup 11:00am–12:00pm; Walter Library 310 UL |
For additional information, or to get on our mailing list, contact Kyle (nicko013@umn.edu), Ethan (brow3821@umn.edu), or Andy (zief0002@umn.edu).
Here our some resources from our Fall 2014 presentations. These can help provide a running start in the most essential basics of using R.
Sept 8 | Introduction to RStudio [slides] | [data] |
Sept. 22 | Easy, Beautiful R Documents: R Markdown [slides] | [rmd file] | [bib file] | [csl file] |
Oct. 6 | Data Preparation I: Subsetting and Merging [slides] | [rdata file] |
Oct. 20 | Data Preparation II: Filters, Transformations & Summarization using dplyr [PDF slides] | [R script file] | [rdata file] |
Nov. 3 | Data Preparation III: Reshaping Data [PDF slides] | [R script file] | [rdata file] |
For additional information, or to get on our mailing list, contact Kory (vuexx199@umn.edu), Kyle (nicko013@umn.edu), or Andy (zief0002@umn.edu).