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Faites Attention! Dealing with Inattentive and Insincere Respondents in Experiments

Respondents who don’t pay attention or respond insincerely are in vogue (see the second half of the note). But how do you deal with such respondents in an experiment? To set the context, a toy example. Say that you are running an experiment. And say that 10% of the

The Declining Value of Personal Advice

There used to be a time when before buying something, you asked your friends and peers about advice, and it was the optimal thing to do. These days, it is often not a great use of time. It is generally better to go online. Today, the Internet abounds with comprehensive,

Maximal Persuasion

Say that you want to persuade a group of people to go out and vote. You can reach people by phone, mail, f2f, or email. And the cost of reaching out f2f > phone > mail > email. Your objective is to convert as many people as possible. How would

The Value of Bad Models

This is not a note about George Box’s quote about models. Neither is it about explainability. The first is trite. And the second is a mug’s game. Imagine the following: you get hundreds of emails a day, and someone must manually sort which emails are urgent and which

Snakes on Ladders: Encouraging People to Climb the Engagement Ladder

Marketers love engagement ladders. To increase engagement with a product, many companies segment their users based on usage, for instance, into heavy (super), medium (average), and light, and prod their users to climb the ladder by suggesting they do things that people in the segment above them are doing and

Why do We Fail? And What to do About It?

I recently read Gawande’s The Checklist Manifesto. (You can read my review of the book here and my notes on the book here.) The book made me think harder about failure and how to prevent it. Here’s a result of that thinking. We fail because we don’t

Wanted: Effects That Support My Hypothesis

Do survey respondents account for the hypothesis that they think people fielding the survey have when they respond? The answer, according to Mummolo and Peterson, is not much. Their paper also very likely provides the reason why people don’t pay much attention. Figure 3 provides data on manipulation checks—

Interview with InfoQ

I recently gave an interview to InfoQ about my paper (and associated open source software) on predicting the race and ethnicity of a person using the sequence of characters in a name. Here a relevant excerpt: InfoQ: Can you discuss how we can learn from names? What ML/DL algorithms

Estimating the Trend at a Point in a Noisy Time Series

Trends in time series are valuable. If the cost of a product rises suddenly, it likely indicates a sudden shortfall in supply or a sudden rise in demand. If the cost of claims filed by a patient rises sharply, it plausibly suggests rapidly worsening health. But how do we estimate