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Industry Spotlight: the Auto Industry

The auto industry serves as a perfect exemplar of three key eras of statistics and data science in service of industry: Total Quality Management (TQM) First in Japan, and later in the U.S., the auto industry became an enthusiastic adherent to the Total Quality Management philosophy. Fundamentally, TQM is all about using data to improveContinue reading “Industry Spotlight: the Auto Industry”

Course Spotlight: Deep Learning

Deep learning is essentially “neural networks on steroids” and it lies at the core of the most intriguing and powerful applications of artificial intelligence. Facial recognition (which you encounter daily in Facebook and other social media) harnesses many levels of data science tools, including algorithms that compare images and match those with similar measurements betweenContinue reading “Course Spotlight: Deep Learning”

The Real Facebook Controversy

Cambridge Analytica’s wholesale scraping of Facebook user data is big news now, and people are shocked that personal data is being shared and traded on a massive scale on the internet. But the real issue with social media is not harming to individual users whose information was shared, but sophisticated and sometimes subtle mass manipulationContinue reading “The Real Facebook Controversy”

Masters Programs versus an Online Certificate in Data Science from Statistics.com

We just attended the analytics conference of INFORMS’ (The Institute for Operations Research and the Management Sciences) this week in Baltimore, and they held a special meeting for directors of academic analytics programs to better align what universities are producing with what industry is seeking. The number of such programs is still growing rapidly (>200),Continue reading “Masters Programs versus an Online Certificate in Data Science from Statistics.com”

Course Spotlight: Text Mining

The term text mining is sometimes used in two different meanings in computational statistics: Using predictive modeling to label many documents (e.g. legal docs might be “relevant” or “not relevant”) – this is what we call text mining. Using grammar and syntax to parse the meaning of individual documents – we use the term naturalContinue reading “Course Spotlight: Text Mining”

Quotes about Data Science

“The goal is to turn data into information, and information into insight.” – Carly Fiorina, former CEO, Hewlett-Packard Co. Speech given at Oracle OpenWorld “Data is the new science. Big data holds the answers.” – Pat Gelsinger, CEO, EMC, Big Bets on Big Data, Forbes“Hiding within those mounds of data is knowledge that could change the lifeContinue reading “Quotes about Data Science”

Be Smarter Than Your Devices: Learn About Big Data

When Apple CEO Tim Cook finally unveiled his company’s new Apple Watch in a widely-publicized rollout earlier this month, most of the press coverage centered on its cost ($349 to start) and whether it would be as popular among consumers as the iPod or iMac. Nitin Indurkhya saw things differently. “I think the most significantContinue reading “Be Smarter Than Your Devices: Learn About Big Data”

Twitter Sentiment vs. Survey Methods

Nobody expects Twitter feed sentiment analysis to give you unbiased results the way a well-designed survey will. A Pew Research study found that Twitter political opinion was, at times, much more liberal than that revealed by public opinion polls, while it was more conservative at other times. Two statisticians speaking at the Joint Statistical MeetingsContinue reading “Twitter Sentiment vs. Survey Methods”

Predictive Modeling and Typhoon Relief

The devastation wrought by Super-Typhoon Haiyan in the Philippines is the biggest test yet for the nascent technology of “artificial intelligence disaster response,” a phrase used by Patrick Meier, a pioneer in the field. When disaster strikes, a flood of social media posts and tweets ensues. There is useful information in the data flood, butContinue reading “Predictive Modeling and Typhoon Relief”

Illuminate, Iterate, Involve, Involvement, Iteration, Insight

I did not start off in the field of statistics; my first real job was as a diplomat. And from my undergraduate days I recall a professor who taught a cultural history of Russia. He was one of the world’s top experts. Possessed of a tremendous store of knowledge (a leading author in the field,Continue reading “Illuminate, Iterate, Involve, Involvement, Iteration, Insight”