“In the age of Big Data we often believe that our predictions about the future are better than ever before. But ...in the real world, we often get better results by using simple rules and considering less information.” (From a review of Gerd Gigerenzer’s Data Savvy)…
A famous business school case by Harvard Professor Michael Porter on forecasting chainsaw sales dramatically illustrated the limits of statistical models when common business sense and clear-eyed thinking are missing. In the chainsaw case, students were asked to forecast the future U.S. demand for chainsaws,…
In deployed machine learning pipelines, “drift” is changes in the model environment that cause the model performance to degrade over time. Drift might result from data quality changes. For example, increasing amounts of missing values in the input data. Or a company might alter the…
This week we look at several case studies where success on the AI front was not sufficient to assure longer term business success. Our course spotlight is on: Aug 20 - Sep 17: Introduction to Design of Experiments Learn how to design experiments (especially costly…
Who would have thought that an entire book devoted to the bias-variance tradeoff would make it to the NY Times business best seller list? The book is the recently-published Noise, by Daniel Kahneman, Olivier Sibony and Cass R. Sunstein, and, as of the beginning of…
A common problem in machine learning is the “rare case” situation. In many classification problems, the class of interest (fraud, purchase by a web visitor, death of a patient) is rare enough that a data sample may not have enough instances to generate useful predictions.…
In their book, "Mining Your Own Business," Jeff Deal and Gerhard Pilcher, COO and CEO of Elder Research respectively, describe what I'll call “The Case of the Climbing Churn.” Churn is when a subscriber cancels or fails to renew a service or subscription. A successful…
This week we look at odds and betting; our course spotlights are July 23 -Aug 20: SQL - Responsible Data ScienceJuly 30 -Aug 27: SQL - Biostatistics 1 - For Medical Science and Public Health See you in class! - Peter BruceFounder of The Institute for Statistics…
Epidemiological terms are top of mind now, due to the pandemic. Here are two that often confuse: incidence and prevalence. For example, I encountered the following sentence on a popular medical web site: “Knee meniscal injuries are common with an incidence of 61 cases per…
In your introductory statistics class, probability took center stage. Odds were for gamblers. But it turns out odds play an important role in statistics, too. The relationship between the two is simple. To estimate the probability that event “A” will happen, we divide the number…
This week we look at the increasingly important role of data engineers. Our spotlight is on our Programming for Data Science certificate program -you can start in July with July 9 -Aug 6: SQL - Introduction to Database Queries See you in class! - Peter…
An often-overlooked basic part of learning new things is vocabulary: if you don’t fully understand the meaning of terms, you are handicapped. Worse, if you think you do understand, but that understanding is wrong, you are deprived of the ability to identify the gap in…
This week we discuss data leaks, which can render apparently well-performing machine learning models useless. Our spotlight is on the Thomas Edison University Data Science Analytics Master’s Program, which was developed in partnership with Statistics.com See you in class! - Peter BruceFounder of The Institute…
He spoke with Val Woodside, our Customer Success Specialist at Statistics.com about his experience in the certificate program. Tell us about your experience at Statistics.com? It was excellent. For me it was the first time that I studied through this online process. You have to…
