Fundamental mathematics and statistics are used by the great majority of the workforce, without their thinking of themselves in any way as mathematicians or statisticians. Recent study of Massey University estimated that more than 85% of the New Zealand work force is involved in simple forms of measurement and estimation, more than 67% is involved in some form of data collection and interpretation, and over 50% is responsible for some form of inventory or money management. Similar data can be found in other Asian, European and African countries of the world. Usually, the mathematical activity is restricted to well-defined tasks - computations, measurements, plotting and interpretation of simple graphs - carried out on a routine basis, without the person doing the work being able easily to modify their task in response to changing circumstances. Most of the tasks would be within the scope of the regular school programme. There is then a very wide spectrum of mathematical tasks embedded into different professional fields, for example, finance and accounting, engineering science and architecture technology, business and management, agriculture, medicine, physical, biological and social sciences, etc. Almost universally, the computations for these tasks are no longer handled manually, but are coded into different types of software - spreadsheets, statistical packages, purpose-built packages for computer-aided design, inventory control, forecasting etc. The mathematical skills are required not in operating the computer terminal, but in interpreting the output, checking that requirements on input data are properly satisfied, understanding the things that can go wrong, adapting the use of the software to the particular requirements of the problem at hand. At the less mathematical end of the spectrum, the persons undertaking these tasks may not be easily able updating the procedures they use to cope with new or changing circumstances. At the more mathematical end, the persons may spend much of their time developing such modifications or guiding and advising less confident staff. As in any professional task in the field of medical science, agricultural science, engineering science and technology, the value and quality of the service provided depends greatly on the quality of the evaluator/estimator and the perspective they are able to bring to the problem as a result of their background knowledge and experience. In this respect, the mathematical training of the staff concerned may vary from, at the lower end, a university service course on basic mathematics or statistics, topped up by specific applications courses in the subject area, to, at the upper end, a full masters degree or higher in one of the mathematical sciences.
Finally, there is a logical consistency in which virtually all major scientific and technological advances have required appropriate mathematical tools or theories for their development. At some stage, these tools or theories were themselves the subject of independent mathematical research.
It is highly expected that the information and exploration of significant results gained through the present special issue will contribute to the world economy, and the following factors likely to affect their role in the future:
• The most important role of mathematics is in underpinning almost all activities in a modern society of science & technology. It operates at many levels and extends across all socio-economic sectors.
• To find a high general level of quantitative literacy; care for data quality and integrity in both public and private sectors;
• To find adequate mathematical expertise available for proper advice and interpretation of quantitative software, and the development, interpretation, and application of quantitative models;
• To recognize that proper uses of computer software and packages for complex or high-consequence analyses requires sound professional knowledge of mathematics and statistics;
• An active core of research mathematicians linking universities, research organizations and research sections of large companies and industries; a strong professional role for mathematical scientists;
• Effective use of quantitative techniques in policy analysis and decision-making;
• School and University programmes which supported and enhanced the development of quantitative and logical skills.
• To show a continued role for mathematics as an underpinning science; computing power as an essential component of mathematics research; an increased demand for statistical skills, including operations research, and process and quality control;
• To show continued and increased demand for mathematical modeling applications and research;
• To show an increased professionalization of mathematics, especially statistics; significant impacts arising from advances in technological data management, including acquisition, coding, storage, retrieval, interrogation, and analysis of large data sets.
Prof. Ram Bilas Misra
State University of New York, Republic of Korea
Dr. R.M.L. Avadh University, Faizabad, U.P. India
Prof. Bijay Singh
Punjab Agricultural University, India
Prof. Chandra K. Jaggi
University of Delhi, New Delhi, India
Avadhesh Kumar Maurya
Gautam Buddha Technical University, Lucknow, U.P., India