Colin Lingwood Mallows

Siddhartha Dalal and James Landwehr

Colin Mallows was born on September 10, 1930, in Great Sampford, a small village in Essex, England. His father was the village policeman and later became chief inspector at the police headquarters in Chelmsford, responsible for education and record-keeping regarding road safety. In this role, his father created statistical procedures, and perhaps this sparked Colin’s interest.

In 1940, at the beginning of the Battle of Britain, Mallows’ parents evacuated him and his brother to Cape Town, South Africa. He returned to England in 1945 and, in 1948, began studying at University College London in the department of mathematics. He soon moved to the department of statistics, founded by Karl Pearson in 1911 as the first statistics department and the place where modern statistics began. When Mallows began his studies, Egon Pearson was the professor and the faculty included F. N. David, N. L. Johnson, and H. O. Hartley. Colin finished his PhD in 1953 under David and Johnson, and all four parts of his thesis were published. For the following two years, he served his national service in the Royal Artillery.

While at University College, he met his wife, Jean, at a local dance in Essex and the first thing he asked her, while the lights were dimmed, was whether she could trust him in the dark. The rest was history. Colin and Jean married in 1956 and continued folk dancing for many years.

Following his graduation, he had one year at University College London, another year at Princeton University where John Tukey recruited him, and another two years at University College. Finally, in 1960 he joined Bell Labs, Murray Hill, New Jersey. He felt he had “lucked into the best job in the world” with early colleagues like John Tukey, Brad Murphy, Martin Wilk, Ram Gnanadesikan, Bill Williams, Dave Brillinger, and Frank Anscombe.

He enjoyed the stimulating environment of Bell Labs due to the highly technical management that allowed researchers to explore new directions without constraints and the presence of a constant stream of new problems and collaborations with colleagues in engineering and the mathematical, physical, and social sciences. He was greatly influenced by Tukey’s pathbreaking work on data analysis and invention of statistical tools such as box plots and stem-and-leaf diagrams. For years, Colin taught data analysis courses based on these and other ideas at Bell Labs.

As the statistical effort grew, he and Gnanadesikan became department heads at Bell Labs and recruited John Chambers, Siddhartha Dalal, Trevor Hastie, Jon Kettenring, Jim Landwehr, Vijay Nair, Yehuda Vardi, and others. In 1995, at one more breakup of AT&T, he joined AT&T Labs, from which he formally retired in 2000 and then began consulting at Avaya Labs (a second-generation spin-off from AT&T).

Colin was a prolific researcher and wrote more than 200 papers and several research notes and was a co-inventor on five patents. He is probably most well known for inventing, with stimulation from Cuthbert Daniels, what came to be known as “Mallows Cp Statistic,” a regression model diagnostic procedure still used every day around the world. He thought Cp should be used only as a descriptive tool to assess whether a set of variables was as good as another one and min Cp should not be used as a criterion.

“A Conversation with Colin L. Mallows” was published in the International Statistical Review in December of 2013. In that conversation, Mallows described his approach to statistical problems, the Bell Labs research environment and how it appealed to him and enabled him to thrive, his work on AT&T regulation issues, and how he approached research and mathematical problems in general.

Besides Cp, he worked on rank models, regression diagnostics, inequalities, robust statistics, experimental designs, matrix methods, privacy and security, combinatorics, and Apollonian packing with numerous colleagues across the world. Some of the problems were purely mathematical, though his approach was unique in that he always tried to think of relevant data that would give him insight into deeper mathematical arguments.

A classic example of this was in the context of a challenging problem with a major prize posed by John Conway on Conway Sequences. Colin solved the problem with his unique insights from data analysis and simulations. He thought statisticians were spending comparatively little time on the so-called “Zeroth problem”—the first problem being the formation of specifications for the data, the second being design procedures for dealing with data that makes sense in context of the specification, and the third being distributional aspects and inference. Before all these, the Zeroth problem involves how one thinks about what data ought to be collected for the problem at hand. He wove these ideas into his Fisher Lecture at the 1997 Joint Statistical Meetings.

He always believed in looking at data before making any assumptions. Thus, he felt uncomfortable with Bayesian assumptions on prior distributions as well as truly believing the distributional model. Nevertheless, he often approached problems from a Bayesian perspective to identify a method of analysis and later would question its assumptions.

He thought statistics was similar to engineering in that in engineering one has to deal with the real world—a bridge either stands up or it doesn’t. In statistics, the procedure either makes sense and helps with the real problems or it doesn’t. He thought the statistics profession has opportunities everywhere, but it has sometimes been unwilling to take the lead on emerging areas such as machine learning. Another concern he had was how best to teach applied statistics in the classroom.

Colin was a fellow of the American Statistical Association, Institute of Mathematical Statistics, and Royal Statistical Society. He was chosen as Fisher Lecturer in 1997 and Deming Lecturer in 2004, and he received the Wilks Memorial Award in 2007. He also received the AT&T Science and Technology medal in 1999.

Colin stayed interested and engaged in research until his final days. In the summer of 2023, he was approached by a psychologist researcher from his Bell Labs days about reviving and revising a technical memorandum they had written and distributed internally at Bell Labs but never published. The revision was completed in August, with the most important change being the addition of data—the original memorandum was purely theoretical. It is currently under review at a psychological journal.

One of his main hobbies was table tennis. He played in a league at a club in Westfield, New Jersey, at least one night a week for more than 50 years and competed in tournaments and league play well into his 80s. Another pleasure was writing limericks for special occasions. Colin and his wife owned a 70-acre farm in northwestern New Jersey for about 20 years. It was heavily wooded, and they raised sheep. Colin fixed fences and really enjoyed cutting down trees.

Colin Mallows died on November 4, 2023, at the age of 93. He is survived by his wife of 67 years, three daughters, eight grandchildren, 14 great-grandchildren, and one great-great grandson.

Download a PDF of Mallows’ key publications by areas of research.

Richard Olshen

ASA Fellow Richard Olshen passed away on November 8, 2023. He was emeritus professor of biomedical data science at Stanford Medicine. As well as being an ASA Fellow, Olshen was a fellow of the Institute for Mathematical Statistics, Institute of Electrical and Electronics Engineers, and the American Association for the Advancement of Science. He was also a Guggenheim Memorial Foundation Fellow.

Olshen’s research was in applications of statistics to medicine and biology, focusing on tree-structured algorithms for classification, regression, survival analysis, and clustering.

Olshen was born in Portland, Oregon, on May 17, 1942. He spent his early years in Chevy Chase, Maryland, and later attended the University of California, Berkeley, where he earned his statistics degree. He finished his PhD in statistics at Yale University, writing his dissertation under the direction of Jimmie Savage and Frank Anscombe.

Learn more about Olshen and download the interview he did with John Rice in 2015 for Statistical Science.