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1. Understanding the Entirety of Modern Informatics.

Author

Cassel, Lillian N.

Subjects
COMPUTER science, INFORMATION technology, MATHEMATICS, ENGINEERING, PHYSICAL sciences, CURRICULUM
Abstract

The field of informatics challenges our ability to classify and describe ourselves. It is both complex and ever changing. In recent years distinct sub areas have identified themselves and begun to specify their place independent of other areas. There are both advantages and disadvantages to this trend. This paper presents the rationale for an effort to keep a comprehensive view of the entirety of informatics, even while the various components continue to develop. [ABSTRACT FROM AUTHOR]

Published
2007
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2. AUSTRALIAN PRIVATE SCHOOLS, SPECIALIZATION AND CURRICULUM CONSERVATION.

Author

Teese, Richard

Subjects
PRIVATE schools, SCHOOL enrollment, TEACHERS' unions, EDUCATIONAL finance, HUMANITIES, PHYSICAL sciences, MATHEMATICS
Abstract

Focuses on the condition of the private schools in Australia. Increase in the enrollments of private schools; Success of state teacher unions and parents' committees with enrollment impact assessments in preventing funding of new schools or classes; Interpretation of the patterns of specialization in the humanities, the physical sciences and mathematics.

Published
1989
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3. A spatial-type interval-valued median for random intervals

Author

Stefan Van Aelst and Beatriz Sinova

Subjects
Statistics and Probability, Statistics & Probability, random interval, Sample (statistics), WEBER LOCATION PROBLEM, 02 engineering and technology, Type (model theory), 01 natural sciences, Interval valued, 010104 statistics & probability, d(theta)-median, Interval-valued data, Statistics, REGRESSION, 0202 electrical engineering, electronic engineering, information engineering, Sensitivity (control systems), statistical robustness, 0101 mathematics, ESTIMATORS, Statistic, COMPACT, Mathematics, Science & Technology, algorithm, METRICS, Sample mean and sample covariance, MODEL, UNIQUENESS, Outlier, Physical Sciences, 020201 artificial intelligence & image processing, Random interval, sense organs, Statistics, Probability and Uncertainty, SET, WEISZFELD ALGORITHM
Abstract

© 2018 Informa UK Limited, trading as Taylor & Francis Group. To estimate the central tendency or location of a sample of interval-valued data, a standard statistic is the interval-valued sample mean. Its strong sensitivity to outliers or data changes motivates the search for more robust alternatives. In this respect, a more robust location statistic is studied in this paper. This measure is inspired by the concept of spatial median and makes use of the versatile generalized Bertoluzza's metric between intervals, the so-called dθ distance. The problem of minimizing the mean dθ distance to the values the random interval takes, which defines the spatial-type dθ-median, is analysed. Existence and uniqueness of the sample version are shown. Furthermore, the robustness of this proposal is investigated by deriving its finite sample breakdown point. Finally, a real-life example from the Economics field illustrates the robustness of the sample dθ-median, and simulation studies show some comparisons with respect to the mean and several recently introduced robust location measures for interval-valued data. ispartof: STATISTICS vol:52 issue:3 pages:479-502 status: published

Published
2018