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Statistics in an Engineering School in the time of Data Science
Last modified: 2018-06-04
Abstract
Almost twenty years have passed since, in the famous “Two culture†pa-
per appeared on Statistical Science in 2001, Leo Breiman shocked statisticians all over the world by accusing them of producing “irrelevant theory†and “questionable conclusions†and of abstaining “from working on a large range of interesting current problems.†Breiman was a former pure leading probabilist turned applied statistician turned data scientist, a quite interesting curriculum. On the other hand, the author continued, “Algorithmic modeling, both in theory and practice, has devel-
oped rapidly in fields outside statisticsâ€. That paper was announcing a revolutionary tide which has changed the way we think about data and Statistics. Starting from the technological center of the world, the tide has now reached our departments and our society and we are confronted with it every single working day. As statisticians working within a large community of engineers, computer scientists, physicists and mathematicians engaged in Data Science, we would like to comment on some aspects of such confrontation and to suggest ways statisticians can still be useful today
in a multidisciplinary environment.
per appeared on Statistical Science in 2001, Leo Breiman shocked statisticians all over the world by accusing them of producing “irrelevant theory†and “questionable conclusions†and of abstaining “from working on a large range of interesting current problems.†Breiman was a former pure leading probabilist turned applied statistician turned data scientist, a quite interesting curriculum. On the other hand, the author continued, “Algorithmic modeling, both in theory and practice, has devel-
oped rapidly in fields outside statisticsâ€. That paper was announcing a revolutionary tide which has changed the way we think about data and Statistics. Starting from the technological center of the world, the tide has now reached our departments and our society and we are confronted with it every single working day. As statisticians working within a large community of engineers, computer scientists, physicists and mathematicians engaged in Data Science, we would like to comment on some aspects of such confrontation and to suggest ways statisticians can still be useful today
in a multidisciplinary environment.
References
Breiman, L.: Statistical Modeling: The Two Cultures (with comments and
a rejoinder by the author). Statist. Sci.16, 3, 199-231 (2001).
a rejoinder by the author). Statist. Sci.16, 3, 199-231 (2001).
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