Williams Professor Shares Stories of Statistical Sins | Features - The Octant

“Whether you have set your mind to an MCS degree or dread your bi-weekly QR lessons, it is clear that data analysis is essential to research in almost every field.” according to Ryan Ma, Author at The Octant.

Williams Professor Shares Stories of Statistical Sins
Photo: Ryan Ma

“Why is a data science book like a jazz piece written by Bill Clinton’s Vice President? Both are filled with Al Gore Rhythms.” With a bad dad joke, Professor Richard D. De Veaux from Williams College kickstarted a lighthearted but informative Rector’s Tea on August 21, where he shared lessons on statistics that he had learned in his personal, professional, and academic life.

The talk, aptly titled “The Seven Deadly Sins of Data Science– and How to Avoid Them,” was held in the evening at Cendana Rector’s Commons. Among first-year students taking the Common Curriculum, Prof. De Veaux is known as an author of their Quantitative Reasoning (QR) textbook, “Stats: Data and Models”. As a statistician, his illustrious career has brought him to Stanford, Princeton, and the consulting industry. He has also patented several statistical methods, and he is currently the Vice-President of the American Statistical Association.

At the talk, Prof. De Veaux explored a crucial yet unsettling question – what could go wrong in statistical research? Given the ubiquity of big data in academia and industry, this question concerns all of us regardless of which field we are pursuing.

There is a difference between data scientists and statisticians, he said. The problem with data scientists is that they do not think enough about the problem they are solving. “What do statisticians bring to data science? They ask questions,” he said...

As students, we may be surprised that seasoned statisticians would make such rookie-level mistakes. After all, the vulnerability of mean values to extreme outliers would have been covered in any introductory statistics class. This story shows that data is hardly as objective as many imagine it to be.
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Source: The Octant