Harry V. Roberts

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Harry V. Roberts
Scientific career
Doctoral students Eugene Fama

Harry V. Roberts (1923–2004), American statistician, was a distinguished teacher and a pioneer in looking at the applications of Bayesian statistics to business decision making and in Total Quality Management.

A statistician is a person who works with theoretical or applied statistics. The profession exists in both the private and public sectors. It is common to combine statistical knowledge with expertise in other subjects, and statisticians may work as employees or as statistical consultants.

Bayesian statistics is a theory in the field of statistics based on the Bayesian interpretation of probability where probability expresses a degree of belief in an event, which can change as new information is gathered, rather than a fixed value based upon frequency or propensity. The degree of belief may be based on prior knowledge about the event, such as the results of previous experiments, or on personal beliefs about the event. This differs from a number of other interpretations of probability, such as the frequentist interpretation that views probability as the limit of the relative frequency of an event after a large number of trials.

Roberts began teaching at the University of Chicago Graduate School of Business in 1949 as an instructor of statistics. He was promoted to assistant professor in 1951. He earned his Ph.D. from the University of Chicago in 1955, and was appointed associate professor. He was made full professor in 1959, and was named Sigmund E. Edelstone Professor of Statistics and Quality Management in 1991. In 1997, Roberts was awarded the Norman Maclean Faculty Award from the University of Chicago for his contributions to teaching and to the student experience on campus. In recognition of his career achievements, the Chicago chapter of the American Statistical Association created the Harry V. Roberts Statistical Advocate Award, first given in January 2002.

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His varied research interests also included interactive computing; time series analysis; the relation between statistical theory and practical decision making; survey methodology and practice; and productivity and quality improvement.

Interactive computing software which accepts input from humans as it runs

In computer science, interactive computing refers to software which accepts input from the user as it runs.

The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches. Within a given approach, statistical theory gives ways of comparing statistical procedures; it can find a best possible procedure within a given context for given statistical problems, or can provide guidance on the choice between alternative procedures.

Roberts was the co-author of many influential publications, including two groundbreaking books: Basic Methods of Marketing Research (with James Lorie) and the textbook, Statistics: A New Approach (with W. Allen Wallis). He also co-authored an early work on the random walk hypothesis of stock market prices, “Differencing of Random Walks and Near Random Walks,” with Nicholas Gonedes, published in the Journal of Econometrics in 1977.

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Roberts was an early computer enthusiast, and was especially interested in developing computer methods for statistical analysis. In the late 1960s, Roberts, in collaboration with his wife June and Robert Ling, developed a statistics package called Interactive Data Analysis (IDA), used for statistical instruction at a number of top business schools.

Toward the end of his career, Roberts helped develop a curriculum in Total Quality Management at Chicago GSB and co-authored Quality is Personal: A Foundation for Total Quality Management (with B. F. Sergesketter). This was a novel application of TQM methods to self-improvement, reminiscent of self-experimentation.

Self-experimentation refers to the special case of single-subject research in which the experimenter conducts the experiment on themself. Usually this means that a single person is the designer, operator, subject, analyst, and user or reporter of the experiment.

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