Blog Archives

Visualization Series: Using Scatterplots and Models to Understand the Diamond Market (so You Don’t Get Ripped Off)

January 19, 2014
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Visualization Series: Using Scatterplots and Models to Understand the Diamond Market (so You Don’t Get Ripped Off)

My last post railed against the bad visualizations that people often use to plot quantitive data by groups, and pitted pie charts, bar charts and dot plots against each other for two visualization tasks.  Dot plots came out on top. … Continue reading →

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Streamline Your Mechanical Turk Workflow with MTurkR

June 24, 2013
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Streamline Your Mechanical Turk Workflow with MTurkR

I’ve been using Thomas Leeper‘s MTurkR package to administer my most recent Mechanical Turk study—an extension of work on representative-constituent communication claiming credit for pork benefits, with Justin Grimmer and Sean Westwood.  MTurkR is excellent, making it quick and easy to: test … Continue reading →

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Generating Labels for Supervised Text Classification using CAT and R

February 4, 2013
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Generating Labels for Supervised Text Classification using CAT and R

The explosion in the availability of text has opened new opportunities to exploit text as data for research. As Justin Grimmer and Brandon Stewart discuss in the above paper, there are a number of approaches to reducing human text to … Continue reading →

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Working with Bipartite/Affiliation Network Data in R

September 30, 2012
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Working with Bipartite/Affiliation Network Data in R

Data can often be usefully conceptualized in terms affiliations between people (or other key data entities). It might be useful analyze common group membership, common purchasing decisions, or common patterns of behavior. This post introduces bipartite/affiliation network data and provides … Continue reading →

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Visualization series: Insight from Cleveland and Tufte on plotting numeric data by groups

March 4, 2012
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Visualization series: Insight from Cleveland and Tufte on plotting numeric data by groups

After my post on making dotplots with concise code using plyr and ggplot, I got an email from my dad who practices immigration law and runs a website with a variety of immigration resources and tools.  He pointed out that the … Continue reading →

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Putting it all together: concise code to make dotplots with weighted bootstrapped standard errors

November 27, 2011
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Putting it all together: concise code to make dotplots with weighted bootstrapped standard errors

I analyze a lot of experiments and there are many times when I want to quickly look at means and standard errors for each cell (experimental condition), or the same for each cell and individual-level attribute level (e.g., Democrat, Independent, … Continue reading →

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Map the distribution of your sample by geolocating ip addresses or zip codes

September 18, 2011
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Map the distribution of your sample by geolocating ip addresses or zip codes

Yesterday I wanted to create a map of participants from a study on social media and partisan selective exposure that Sean Westwood and I ran recently, with participants from Amazon’s Mechanical Turk.  We recorded ip addresses for each Turker participant, so … Continue reading →

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