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Michael Levy's blog

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Tidyverse Tutorial

By Michael Levy - Posted on 17 October 2016

Last week, I gave an overview of bunch of tidyverse packages (tibble, dplyr, tidyr, ggplot, readr, purrr) to the Davis R-Users’ Group. Here is that talk (and since videos don’t display everywhere this blog is syndicated, here is the YouTube link).

I mention early in the talk that the github_markdown specification in the YAML header produces a conveniently GitHub-renderable markdown file – here that is if you’d like to follow along, or you can download the rendered R Notebook (nb.html) file, which itself includes the R Markdown file (Awesome! In the upper right of the html file, click “Code” -> “Download Rmd”).

useR! talk on teaching R

By Michael Levy - Posted on 05 July 2016

Here is a video recording of my talk from useR! 2016 on teaching R. It’s nominally about teaching a lot of students in an intensive format, but I think almost everything translates to traditional classes. If for whatever reason this video isn’t working out for you, here is the source.

This talk was just one in a great session. I’d highly recommend:

A Shiny app to help interpret GW-Degree estimates in ERGMs

By Michael Levy - Posted on 26 June 2016

Most researchers are misinterpreting geometrically weighted degree (GWD) estimates in exponential random graph models (ERGMs) of networks. By a 3:1 ratio papers cite positive estimates of GWD as indicative of a popularity or centralization force; in fact, positive estimates indicate dispersion of edges.

Shiny app

Here is a Shiny app that allows you to examine the effects of GWD parameter and decay-parameter values on network degree distributions. On the app’s other tabs, it provides some intuition on how the GWD statistic works and how GWD and GWESP – which is used to model triadic closure – are confounded.

Poster

I presented this research at the 2016 Political Networks conference. Check out the poster, which includes a literature review showing how prevalent this mistake is, by clicking on the image.

Teaching R to 200 students in a week

By Michael Levy - Posted on 20 September 2015

I just taught a week-long "R Bootcamp" to 200 R newbies. It went quite well, and I thought it would be valuable to jot down some thoughts on what worked and what I might change if doing it again.

Teaching R to 200 students in a week

By Michael Levy - Posted on 19 September 2015

I just taught a week-long “R Bootcamp” to 200 R newbies. It went quite well, and I thought it would be valuable to jot down some thoughts on what worked and what I might change if doing it again.

The course design and my approach to teaching scientific computing in general have been deeply shaped by Greg Wilson and the Software Carpentry pedagogy, and this was an experiment in scaling that approach. Software/Data Carpentry workshops are typically two days, cover 3-4 computational tools, and have a student:instructor/assistant ratio of about 8:1. Here, we had five days, just one computational tool, and a ratio of about 50:1. The mission was also different. My goals, in descending priority, were to get students:

All 15 home teams win! What are the odds?

By Michael Levy - Posted on 12 August 2015

My dad just sent me an article saying that yesterday was the first time in the modern history of Major League Baseball that all 15 home teams won in a single day. Seems pretty incredible, right? To get 15 of 15 winners in a 50/50 contest is a 0.5^15 = 1-in-32,768 shot. To get a better sense of just how rare an event this is, we need to know two things: 1. how often is it possible for it to happen (i.e. all 30 teams play in a day), and 2. when it’s possible, what is the probability of it happening (i.e. all 15 home teams winning).

What we're reading -- and how it ties us together

By Michael Levy - Posted on 29 March 2015

Network of an interdisciplinary environmental social science lab as tied together by the journals we read. A few key journals, especially Social Networks, hold us together. R code follows.

The Center for Environmental Policy and Behavior, my grad lab, is remarkably interdisciplinary. For some sense of our breadth, consider that our nine core graduate students represent five different graduate programs: Ecology, Geography, Hydrology, Political Science, and Transportation Technology and Policy. That's great for many reasons, not least that it's an intellectually exciting environment in which to live, but it sometimes leaves me wondering what ties us together. So I thought I'd see if the journals we read could answer that question.

What we're reading -- and how it ties us together

By Michael Levy - Posted on 28 March 2015

tl;dr: Network of an interdisciplinary environmental social science lab as tied together by the journals we read. A few key journals, especially Social Networks, hold us together. R code follows.

The Center for Environmental Policy and Behavior, my grad lab, is remarkably interdisciplinary. For some sense of our breadth, consider that our nine core graduate students represent five different graduate programs: Ecology, Geography, Hydrology, Political Science, and Transportation Technology and Policy. That’s great for many reasons, not least that it’s an intellectually exciting environment in which to live, but it sometimes leaves me wondering what ties us together. So I thought I’d see if the journals we read could answer that question.

Social science, all shook up

By Michael Levy - Posted on 09 October 2014

The Times Higher Education recently published an article titled Do the social sciences need a shake up? which is a response of sorts to Nicholas Christakis' NY Times op-ed, Let's shake up the social sciences. The central thesis of both is that the social sciences have stagnated, largely because of disciplinary silos, and would better serve society if reorganized. Here are my thoughts as a recent transplant from the biophysical to social sciences.

On the Christakis piece:

Social science all shook up

By Michael Levy - Posted on 08 October 2014

The Times Higher Education recently published an article titled Do the social sciences need a shake up? which is a response of sorts to Nicholas Christakis’ NY Times op-ed, Let’s shake up the social sciences. The central thesis of both is that the social sciences have stagnated, largely because of disciplinary silos, and would better serve society if reorganized. Here are my thoughts as a recent transplant from the biophysical to social sciences.

On the Christakis piece:

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