04031nam a2200289 i 4500 CSPC 20260922170002.0 260922s2023 nyua b 001 0 eng d 9781984681126 CSPC eng CSPC CSPC rda QA273 .A12 2023 519.2 A77 23 3GE collection on mathematics : probability, uncertainty and quantitative risk. New York : 3GE-Learning, 2023. xii, 268 pages : illustrations ; 27 cm. rdacontent text rdamedia unmediated rdacarrier volume Includes bibliographical references and index. Probability -- Uncertainties in the QRA process -- The use of models in risk analysis -- Expert judgement in risk analysis -- Methods of parameter uncertainty propagation and analysis -- Methods of ranking uncertain parameters -- Quantitative and qualitative data collection. "Probability statistics is a mathematical method that aims at finding out the statistical laws governing natural random phenomena. As science and technology have developed, probability statistics knowledge has gained more and more attention from society, which is widely applied to industrial and agricultural production, the national economy and daily life as well. There are many applications of probability theory. Lotteries, gaming, and other games of chance often use this technique. Lotteries aim to increase chances of winning as much as possible. A larger number of tickets are sold, resulting in more winners, increasing the chances of someone winning. Probability theory is also commonly used in gambling. There are many different ways in which probability can be used in real life, and it can be used almost anywhere that does not have a definite outcome. It is possible to apply probability to a number of things in real life, such as sports, where it can be used to predict if a team will win a match, financial investment such as stocks, as well as decisions in everyday life, such as how to drive home and what to wear. To support decisions, quantitative risk analyses (QRAs) should provide a comprehensive, informative, and balanced picture of risk. It is crucial to properly deal with uncertainty in QRA. Most approaches to treatment of uncertainty seem based on the premise that uncertainty is related to the probability and expected values calculated. As a result, it is difficult to communicate what the analysis results mean, and weakened conclusions can easily result if large uncertainties are involved. This E-Collection on Probability, Uncertainty and Quantitative Risk covers the fundamental problems related to uncertainty in quantitative risk analyses, used in decision making are presented and discussed, together with the different types of uncertainty that are introduced in the various stages of an analysis. Because probabilities are so important in our analysis of risk, professionals in a wide range of specialties study probability. Weather experts use probability to derive the percentages given in their forecasts. Medical researchers use probability theory in their study of the effectiveness of new drugs and surgeries. Wall Street firms hire mathematicians to apply probability in the study of investments. The insurance industry has a long tradition of using probability to manage its risks. This collection aims to report significant developments in modern probability theory, its relation to stochastic analysis and statistics, stochastic processes, their dynamics and control, as well as applications in domains such as finance, economics, biology, computer science, and the corresponding data analysis"-- Back cover. Probabilities. Probabilities Mathematical models. 3G E-Learning. ddc 0 BK A77 23 519.2 CIR 2023 0 0 ddc 0 0 CSPC CSPC CIR 2026-09-22 0 CIR 519.2 A77 2023 032603 2026-09-22 16:45:58 1-1 2026-09-22 BK 33381 33381