I have been meaning to try out the gt package for a while now, but didn’t really have a great use case for it. However over the last few days I have been looking over the useR 2019 schedule and felt like I would have an easier time picking talks yo attend if the schedule was formatted in wide format (talks occurring at the same time in different rooms listed next to each other) as opposed to the long format.
Much has been written in statistics and data science education literature about pedagogical tools and approaches to provide a practical computational foundation for students. However a common friction point for getting students (and faculty) started with computing is installation and setup. If you’ve heard me talk about teaching R, you’ve probably heard me mention the following day one dilemma:
Option 1 😰 Option 2 😎 1.
Citizen Statistician is back from a hiatus! I hope to post more regularly in the coming weeks, including writing a post on converting from WordPress to blogdown.
I have recently been dealing with time zone changes. I’ll say a bit more about it shortly. But first, here is a picture of my 2 year old “dealing” with time zone changes.
His schedule is completely thrown off, he doesn’t know what to do with himself, so he keeps moving around in his room in his sleep.
A little over a year ago, we decided to propose a data visualization course at the first-year level. We had been thinking about this for awhile, but never had the time to teach it given the scheduling constraints we had. When one of the other departments on campus was shut down and the faculty merged in with other departments, we felt that the time was ripe to make this proposal.
**Webinar Series: Data Science Undergraduate Education**
Join the National Academies of Sciences, Engineering, and Medicine for a webinar series on undergraduate data science education. Webinars will take place on Tuesdays from 3-4pm ET starting onSeptember 12 and ending on November 14. See below for the list of dates and themes for each webinar.
This webinar series is part of an input-gathering initiative for a National Academies study on Envisioning the Data Science Discipline: The Undergraduate Perspective.
One of the many nice things about summer is the time and space it allows for blogging. And, after a very stimulating SRTL conference (Statistics Reasoning, Teaching and Learning) in Rotorua, New Zealand, there’s lots to blog about.
Let’s begin with a provocative posting by fellow SRTL-er Tim Erickson at his excellent blog A Best Case Scenario. I’ve known Tim for quite awhile, and have enjoyed many interesting and challenging discussions.
This last weekend I helped Danny Kaplan and Kathryn Kozak (Coconino Community College) put on a StatPREP workshop. We were also joined by Amelia McNamara (Smith College) and Joe Roith (St. Catherine’s University). The idea behind StatPREP is to work directly with college-level instructors, through online and in community-based workshops, to develop the understanding and skills needed to work and teach with modern data.
Danny Kaplan ponders at #StatPREP
One of the most interesting aspects of these workshops were the tutorials and exercises that the participants worked on.
