Blog Archives

Looking for Preference in All the Wrong Places: Neuroscience Suggests Choice Model Misspecification

June 22, 2015
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Looking for Preference in All the Wrong Places: Neuroscience Suggests Choice Model Misspecification

At its core, choice modeling is a utility estimating machine. Everything has a value reflected in the price that we are willing to pay in order to obtain it. Here are a collection of Smart Watches from a search of Google Shopping. You are free to click...

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Statistical Models with a Point of View: First vs. Third Person

June 2, 2015
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Statistical Models with a Point of View: First vs. Third Person

Marketing data can be collected in the first or third person, and we require different statistical models for each point of view.Netflix encourages you to adopt a third-person perspective when it surveys your taste preferences by asking how often you w...

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Top of the Heap: How Much Can We Learn from Partial Rankings?

May 30, 2015
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Top of the Heap: How Much Can We Learn from Partial Rankings?

The recommendation system gives you a long list of alternatives, but the consumer clicks on only a handful: most appealing first, then the second best, and so on until they stop with all the remaining receiving the same rating as not interesting enough...

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Respecting Real-World Decision Making and Rejecting Models That Do Not: No MaxDiff or Best-Worst Scaling

May 26, 2015
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Respecting Real-World Decision Making and Rejecting Models That Do Not: No MaxDiff or Best-Worst Scaling

Utility has been reified, and we have committed the fallacy of misplaced concreteness.As this link illustrates, Sawtooth's MaxDiff provides an instructive example of reification in marketing research. What is the contribution of "clean bathrooms" ...

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Clusters Powerful Enough to Generate Their Own Subspaces

May 20, 2015
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Clusters Powerful Enough to Generate Their Own Subspaces

Cluster are groupings that have no external label. We start with entities described by a set of measurements but no rule for sorting them by type. Mixture modeling makes this point explicit with its equation showing how each measurement is an independe...

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What is Data Science? Can Topic Modeling Help?

May 13, 2015
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What is Data Science? Can Topic Modeling Help?

Predictive analytics often serves as an introduction to data science, but it may not be the best exemplar given its long history and origins in statistics. David Blei, on the other hand, struggles to define data science through his work on topic modeli...

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Centering and Standardizing: Don’t Confuse Your Rows with Your Columns

May 11, 2015
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Centering and Standardizing: Don’t Confuse Your Rows with Your Columns

R uses the generic scale( ) function to center and standardize variables in the columns of data matrices. The argument center=TRUE subtracts the column mean from each score in that column, and the argument scale=TRUE divides by the column standard devi...

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What Can We Learn from the Apps on Your Smartphone? Topic Modeling and Matrix Factorization

May 8, 2015
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What Can We Learn from the Apps on Your Smartphone? Topic Modeling and Matrix Factorization

The website for The Burning House begins with a simple question:If your house was burning, what would you take with you? It's a conflict between what's practical, valuable and sentimental. What you would take reflects your interests, background and pri...

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Clusters May Be Categorical but Cluster Membership Is Not All-or-None

May 4, 2015
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Clusters May Be Categorical but Cluster Membership Is Not All-or-None

Very early in the study of statistics and R, we learn that random variables can be either categorical or continuous. Regrettably, we are forced to relearn this distinction over and over again as we debug error messages produced by our code (e.g., ...

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Modeling the Latent Structure That Shapes Brand Learning

April 29, 2015
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Modeling the Latent Structure That Shapes Brand Learning

What is a brand? Metaphorically, the brand is the white sphere in the middle of this figure, that is, the ball surrounded by the radiating black cones. Of course, no ball has been drawn, just the conic thorns positioned so that we construct the sphere ...

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