On the Selection of Distributions for Stochastic Variables

One of the main steps in an uncertainty analysis is the selection of appropriate probability distribution functions for all stochastic variables. In this paper, criteria for such selections are reviewed, the most important among them being any a priori knowledge about the nature of a stochastic variable, and the Central Limit Theorem of probability theory applied to sums and products of stochastic variables. In applications of these criteria, it is shown that many of the popular selections, such as the uniform distribution for a poorly known variable, require far more knowledge than is actually available. However, the knowledge available is usually sufficient to make use of other, more appropriate distributions. Next, functions of stochastic variables and the selection of probability distributions for their arguments as well as the use of different methods of error propagation through these functions are discussed. From these evaluations, priorities can be assigned to determine which of the stochastic variables in a function need the most care in selecting the type of distribution and its parameters. Finally, a method is proposed to assist in the assignment of an appropriate distribution which is commensurate with the total information on a particular stochastic variable, and is based on the scientific method. Two examples are given to elucidate the method for cases of little or almost no information.     

A Little Bit of Sugar: Integrated Service-Learning Courses

Approaches to integrated service learning are detailed for three courses—Organizational Theory, Land Use and Environmental Dispute Resolution, and Mediation Skills. The focus of this paper is on the process of integration rather than the specifics of the courses. A faculty member interested in developing a service-learning component in a course is advised to (1) publicly identify the course as one that includes a service-learning experience, (2) be passionate, organized, flexible, and experienced, (3) establish an excellent relationship with a community agency, (4) be flexible about course content and schedule, (5) recognize that some students may have problems with an experience-based approach to learning, and (6) conduct periodic evaluations of all stages of the service-learning experience.     

Achieving high quality and long‐lasting matches in youth mentoring programmes: a case study of 4Results mentoring

Mentoring programmes show significant promise for enhancing the well‐being of youth with complex needs. Research indicates that high quality mentoring, although difficult to achieve, positively impacts youth development across behavioural, social, emotional and academic domains. The difficulty of sustaining long‐term matches between mentors and youth, however, remains an important concern for the field of mentoring, as foreshortened matches can be harmful to youth. The 4Results mentoring programme has been identified as a Promising Practice through the Washington State Inventory of child‐serving behavioural and mental health programmes and has developed a unique infrastructure to support critical programme values such as match longevity. In 7 years, the programme has successfully retained 98% of mentors for at least 1 year with an average match length of 3.7 years. The following article describes the programme's guiding philosophy and approach to recruiting and training mentors in the context of existing best practices research.     

Use of Fractals to Estimate Environmental Dilution Factors in River Basins

Every source of liquid pollutants lies somewhere on a watershed. Leachwaters derived from water percolating through solid waste deposits and liquid effluents from industry are diluted on their way down the river until they interact with man or particular environmental systems. This environmental dilution of potentially toxic effluents has to be estimated in assessing health and environmental risks. The problem for the risk assessor is to find an appropriate mathematical model. In this paper, the recent mathematical theory of fractal objects is used to demonstrate that, within certain limits, rivers of all lengths and their river basins are self-similar. Simple general relations exist, therefore, between the length and drainage area of rivers both large and small. These relations and a few additional assumptions are then used to derive an improved set of models for estimating environmental dilution of some pollutants.     

Sozioökonomische Entwicklung und Wertvorstellungen in elf Regionen der Türkei

Being an official EU candidate country since 2005 Turkey has also become an interesting object of investigation for empirical social science, especially in the field of value research. In this article we examine value orientations in different regions of Turkey. Contrary to previous country-comparing studies our regional approach accounts for the immense developmental gaps which exist within Turkey. In line with central assumptions of modernization theory we expect values of tolerance and individual autonomy in high developed regions and, on the other side, dogmatic beliefs, intolerance and authoritarian attitudes being predominant in weaker developed regions. First, regional stages of modernization are specified using macro indicators like GDP, education, urbanity, the occupational structure, and fertility rate from the official statistics of Turkey. The regional spectrum varies from extremely poor developed rural-agrarian regions in the east to industrialized regions with high degrees of urbanization up to the rich regions in the west with well developed infastructure and service sector. Second, Multiple Correspondence Analyses carried out with data from the European Values Study 2000 show that value differences concerning democratic culture, religiosity, secularity and sexual tolerance occur as expected according to socio-economic disparities between regions. Additionally, we find evidence that independent from socio-economic factors value orientations of people are also shaped by other influences like the minority situation or political stability in a region.     

Error Propagation for Large Errors

An essential facet of a risk assessment is the correct evaluation of uncertainties inherent in the numerical results. If the calculation is based on an explicit algebraic expression, an analytical treatment of error propagation is possible, usually as an approximation valid for small errors. In many instances, however, the errors are large and uncertain. It is the purpose of this paper to demonstrate that despite large errors, an analytical treatment is possible in many instances. These cases can be identified by an analysis of the algebraic structure and a detailed examination of the errors in input parameters and mathematical models. From a general formula, explicit formulas for some simple algebraic structures that occur often in risk assessments are derived and applied to practical problems.     

Use of Risk Assessment Methods in the Certification of Decontaminated Buildings

Accidental events such as fires, explosions, and leaks often result in large-scale contaminations of buildings with toxic chemicals. After decontamination, the certification for original use requires testing for residual contamination. The two basic kinds of sampling plans in use up to recently both fall short of the required performance. Their deficiencies are analyzed in terms of the scientific questions implicit in both the sampling plan and the subsequent statistical evaluation. A sampling strategy of a new kind is proposed and discussed in the same context. It is motivated by concern for the long-term safety of the building's occupants and is, therefore, based on factors important in risk assessment. Three different sampling plans are derived in the framework of this methodology, two of which have already been used in actual certification proceedings.