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Gaurav

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Some Facts About Indian Polling Stations

Of the 748,584 polling stations for which we have self-reported data on building conditions, nearly 24% report having Internet. A similar number report having “Landline Telephone/Fax Connection.” 97.7% report having toilets for men and women. 2.6% report being in a “dilapidated or dangerous” building. 93.2%

Growth Funnels

You spend a ton of time building a product to solve a particular problem. You launch. Then, either the kinds of people whose problem you are solving never arrive or they arrive and then leave. You want to know why because if you know the reason, you can work to

Conscious Uncoupling: Separating Compliance from Treatment

Let’s say that we want to measure the effect of a phone call encouraging people to register to vote on voting. Let’s define compliance as a person taking the call (like they do in Gerber and Green, 2000, etc.). And let’s assume that the compliance rate is

Prediction Errors: Using ML For Measurement

Say you want to measure how often people visit pornographic domains over some period. To measure that, you build a model to predict whether or not a domain hosts pornography. And let’s assume that for the chosen classification threshold, the False Positive rate (FP) is 10\% and the False

Technical Leadership: Building Great Teams and Products

Companies bet on people. They bet that the people they have hired will figure out the problems and their solutions. To make the bet credible, the golden rule is to hire competent people. Other virtues matter, but competence generally matters the most in technical roles. Once you have made the

Comparing Ad Targeting Regimes

Ad targeting is often useful when you have multiple things to sell (opportunity cost), when the cost of running an ad is non-trivial, when an irrelevant ad reduces your ability to reach the user later, or any combination of the above. (For a more formal treatment, see below.) targetingtargeting.pdf133

What's Relevant? Learning from Organic Growth

Say that we want to find people to whom a product is relevant. One way to do that is to launch a small campaign advertising the product and learn from people who click on the ad, or better yet, learn from people who not just click on the ad but

Sometimes Scientists Spread Misinformation

To err is human. Good scientists are aware of that, painfully so. The model scientist obsessively checks everything twice over and still keeps eyes peeled for loose ends. So it is a shock to learn that some of us are culpable for spreading misinformation. Ken and I find that articles

The New Unit of Scientific Production

One fundamental principle of science is that there is no privileged observer. You get to question what people did. But to question, you first must know what people did. So part of good scientific practice is to make it easy for people to understand how the sausage was made—how

Quality Data: Plumbing ML Data Pipelines

What’s the difference between a scientist and a data scientist? Scientists often collect their own data, and data scientists often use data collected by other people. That is part jest but speaks to an important point. Good scientists know their data. Good data scientists must know their data, too.