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Dan Saber

Fear, loathing, Data Science

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danielsaber

For The Economist: Corporate Wokeness and Campaign Finance

I was interested in whether "woke" companies donate disproportionately to Democrats, or if their embrace of progressive causes is one big branding exercise. The answer? Kinda both! I'm unbelievably proud to say that my findings were published in this week's... Continue Reading →

Partner-Driven A/B Testing at Coursera

I recently attended the Data Science Innovation in eLearning Conference (hosted by Udemy and Zoomi), where I gave a lightning talk on the way we're scaling up A/B testing at Coursera by empowering our university partners to run their own experiments. Check... Continue Reading →

Time Keeps on Slipping: Exploiting Time for Causal Inference with Difference-in-Differences and Panel Methods

Note: This post assumes a passing familiarity with linear regression. Aside from that, it's a highly applied intro to D-in-D regression and panel data techniques. In Due Time In one of my favorite episodes of Futurama, the universe experiences "time skips."... Continue Reading →

For Inside Big Data: Making the Leap from Data Science Hopeful to Practioner

I wrote a post for Inside Big Data on transitioning into Data Science -- a topic I'm actually qualified to give advice on! It’s a familiar dilemma. You’ve done your research, read some books, taken some online classes – and at long... Continue Reading →

A Dramatic Tour through Python’s Data Visualization Landscape (including ggplot and Altair)

Why Even Try, Man? I recently came upon Brian Granger and Jake VanderPlas's Altair, a promising young visualization library. Altair seems well-suited to addressing Python's ggplot envy, and its tie-in with JavaScript's Vega-Lite grammar means that as the latter develops new... Continue Reading →

Analyze Your Experiment with a Multilevel Logistic Regression using PyMC3​

Note: In this post, I assume some familiarity with PyMC. If you need to get up to speed in a hurry and you're familiar with linear regression, go here for a tutorial. Alternatively, you can read for the methodological intuition,... Continue Reading →

Using Data to Hold Crappy Businesses Accountable (Airline Edition)

Contextualizing My Vendetta I've been on a streak of bad flights lately. The last two, in particular, were horrible -- and not horrible in the standard "cramped seats/rubbery food/my-God-that-smell" way. Horrible due to (A) an unexplained cancellation, which turned my 12-hour... Continue Reading →

The Digital Age is Killing the Middle Class: Reconsidering Jaron Lanier’s 2013 Argument in Light of 2016 Election Nonsense

I. I recently wandered down a Google Black Hole on The Skills Gap, hoping to see if economists had come to a consensus on whether it was a real thing or Convenient-sounding Story. While there, I found an interview that... Continue Reading →

Ford Purgatory: Busted Transmissions and Short-Term Thinking

I. Upon completing college, I joined the Treasury Department. (No, I didn’t.) But I did help them bolster the once-proud, then-crumbling pillars of the American Economy: too-big-to-fail banks and car companies. Concretely, I bought a Ford Focus. I’d read Consumer... Continue Reading →

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