Książki na temat „Uncertainty”

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1

Dow, Sheila C. Uncertainty about uncertainty. Stirling: Dept. of Economics, University of Stirling, 1993.

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Briggs, William. Uncertainty. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39756-6.

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Michael, Larsen. Uncertainty. London: Sceptre, 1997.

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Esst, Garrison. Uncertainty. [Denver, Colo.]: Denver Center Theatre Company, 1992.

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Sanz, Yolanda Ortega. Uncertainty. Redaktor International Architectural Exhibition (17th : 2021 : Venice, Italy). Barcelona]: Fundación Arquia, 2021.

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6

MacAskill, Michael. Moral Uncertainty. Oxford: Oxford University Press, 2020.

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7

Garvey, Bruce, Dowshan Humzah i Storm Le Roux. Uncertainty Deconstructed. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08007-4.

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8

Jeschke, Sabina, Eva-Maria Jakobs i Alicia Dröge, red. Exploring Uncertainty. Wiesbaden: Springer Fachmedien Wiesbaden, 2013. http://dx.doi.org/10.1007/978-3-658-00897-0.

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9

Osman, Magda. Controlling Uncertainty. Oxford, UK: Wiley-Blackwell, 2010. http://dx.doi.org/10.1002/9781444328226.

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10

Rautzenberg, Markus. Framing Uncertainty. London: Palgrave Macmillan UK, 2020. http://dx.doi.org/10.1057/978-1-137-59521-8.

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11

Brandolini, Silva Marzetti Dall’Aste, i Roberto Scazzieri, red. Fundamental Uncertainty. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230305687.

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12

Lindley, Dennis V. Understanding Uncertainty. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470055480.

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Lindley, Dennis V., red. Understanding Uncertainty. Hoboken, New Jersey: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118650158.

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14

Liu, Baoding. Uncertainty Theory. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13959-8.

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Liu, Baoding. Uncertainty Theory. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39987-2.

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16

Soize, Christian. Uncertainty Quantification. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54339-0.

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17

Dror, Moshe, Pierre L’Ecuyer i Ferenc Szidarovszky, red. Modeling Uncertainty. New York, NY: Springer US, 2002. http://dx.doi.org/10.1007/b106473.

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18

Kreinovich, Vladik, red. Uncertainty Modeling. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51052-1.

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19

Liu, Baoding. Uncertainty Theory. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-44354-5.

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20

American Society of Mechanical Engineers. Test uncertainty. New York, N.Y: American Society of Mechanical Engineers, 2014.

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21

Viaene, Tom, Michiel de Cleene i Max Pinckers. Trigger: Uncertainty. Redaktor Museum voor Fotografie (Antwerp, Belgium). Antwerpen: FOMU, Fotomuseum, 2020.

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22

Uma, Oberoi, i All India Management Association, red. Managing uncertainty. New Delhi: All India Management Association :bAmexcel Publishers, 1999.

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23

Cattaneo, Istituto Carlo, red. Managing uncertainty. New York: Berghahn, 2010.

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24

Jasanoff, Sheila. Uncertainty. Boston Review/Boston Critic Inc., 2021.

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Fittall, Mark. Uncertainty. Independently Published, 2018.

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26

Uncertainty. Springer, 2016.

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27

Kampourakis, Kostas, i Kevin McCain. Uncertainty. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190871666.001.0001.

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Scientific knowledge is the most solid and robust kind of knowledge that humans have because of its inherent self-correcting character. Nevertheless, anti-evolutionists, climate denialists, and anti-vaxxers, among others, question some of the best-established scientific findings, making claims unsupported by empirical evidence. A common aspect of these claims is reference to the uncertainties of science concerning evolution, climate change, vaccination, and so on. This is inaccurate: whereas the broad picture is clear, there will always exist uncertainties about the details of the respective phenomena. This book shows that uncertainty is an inherent feature of science that does not devalue it. In contrast, uncertainty advances science because it motivates further research. This is the first book on this topic that draws on philosophy of science to explain what uncertainty in science is and how it makes science advance. It contrasts evolution, climate change, and vaccination, where the uncertainties are exaggerated, and genetic testing and forensic science, where the uncertainties are usually overlooked. The goal is to discuss the scientific, psychological, and philosophical aspects of uncertainty in order to explain what it really is, what kinds of problems it actually poses, and why in the end it makes science advance. Contrary to public representations of scientific findings and conclusions that produce an intuitive but distorted view of science as certain, people need to understand and learn to live with uncertainty in science. This book is intended for anyone who wants to get a clear view of the nature of science.
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28

Uncertainty. Ballantine Books, 1998.

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Jasanoff, Sheila. Uncertainty. Boston Review/Boston Critic Inc., 2021.

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Diaz, Jasmine, Emily Salisbury i Cheyenne Kminek. Uncertainty. Independently Published, 2019.

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31

Uncertainty. New York: Knopf Doubleday Publishing Group, 2008.

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32

Uncertainty. Cambridge Univ Pr (Pap Txt), 1992.

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Young, John Northcutt. Uncertainty. Independently Published, 2019.

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Aspers, Patrik. Uncertainty. Oxford University PressNew York, 2024. http://dx.doi.org/10.1093/oso/9780197752753.001.0001.

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Abstract Uncertainty is essential for furthering excitement, creativity, and entertainment, but it is mostly something that actors shun. This book analyses ways in which actors try to increase, deal with, but above all reduce, uncertainty. Uncertainty is an issue facing an individual or an organization, and to decrease their uncertainty, ways to gain more certainty are used. Increased certainty is often the result of knowing more, and scientific production has generated a large systematic body of knowledge that can be put to use. Though each individual faces his or her problems, this book focuses on public solutions that reduce uncertainty for many. How can public means of uncertainty reduction be created, and how can they be used? Concrete solutions to the problem of uncertainty involve informal institutions, for example norms, and formal institutions, for example laws, as well as standards. Much of the uncertainty relates to values, and through markets, competitions, valuations, and contests, it is possible to settle these uncertainties so that knowledge can be used by many to facilitate coordination and action. Organizations, individually or with others, can actively change their environment to reduce their uncertainties rather than merely adapting to them. The publicly available knowledge that is produced is central to building a society that allows communication based on shared ideas and understanding, rather than bubbles, echo chambers, or private truths.
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35

Uncertainty. Lulu Press, Inc., 2018.

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36

Uncertainty. CreateSpace Independent Publishing Platform, 2016.

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37

Jeffers, Susan J. Embracing Uncertainty. Hodder & Stoughton, 2003.

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Liu, Baoding. Uncertainty Theory. Springer, 2014.

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39

Williamson, Roy. Joyful Uncertainty. Society for Promoting Christian Knowledge, 1999.

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40

Kruglanski, Arie. Uncertainty Principle. Penguin Books, Limited, 2023.

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41

Knibbs, Alex. Relative Uncertainty. Independently Published, 2021.

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MacAskill, William, Krister Bykvist i Toby Ord. Moral Uncertainty. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198722274.001.0001.

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Very often, we’re uncertain about what we ought, morally, to do. We don’t know how to weigh the interests of animals against humans, or how strong our duties are to improve the lives of distant strangers, or how to think about the ethics of bringing new people into existence. But we still need to act. So how should we make decisions in the face of such uncertainty? Though economists and philosophers have extensively studied the issue of decision-making in the face of uncertainty about matters of fact, the question of decision-making given fundamental moral uncertainty has been neglected. In this book, philosophers William MacAskill, Krister Bykvist and Toby Ord try to fill this gap. They argue that there are distinctive norms that govern how one ought to make decisions given moral uncertainty. They then defend an information-sensitive account of how to make such decisions according to which the correct way to act in the face of moral uncertainty depends on whether the moral theories in which one has credence are merely ordinal, cardinal, or both cardinal and intertheoretically comparable. They tackle the problem of how to make intertheoretic comparisons, discussing several novel potential solutions. Finally, they discuss implications of their view for metaethics and practical ethics, and show how their account can shed light on the value of moral enquiry.
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Jappelli, Tullio, i Luigi Pistaferri. Lifetime Uncertainty. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199383146.003.0011.

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Lifetime uncertainty represents an additional risk that affects intertemporal choice, because consumers may live longer than expected and run the risk of exhausting the resources accumulated for retirement. Lifetime uncertainty introduces an incentive to consume earlier in life because consumers discount future utility at a higher rate. Second, since in each period there is some positive probability that the consumer will not survive to the next period, the terminal condition on wealth corresponds effectively to a liquidity constraint. Third, with lifetime uncertainty, the decumulation of wealth by the elderly is slower than predicted by the life-cycle model. Finally, the model with lifetime uncertainty generates transfers of wealth across generations even without an express bequest motive, through what we can term involuntary or accidental bequests. The chapter highlights the necessity of accounting for lifetime uncertainty when interpreting empirical age-wealth profiles estimated from microeconomic data.
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Jeffers, Susan. Embracing Uncertainty. Hodder Mobius, 2003.

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Association, All India Management. Managing Uncertainty. Excel Books, 2002.

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Liu, Baoding. Uncertainty Theory. Springer, 2014.

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47

Uncertainty Theory. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73165-8.

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48

Esposito, Elena. Predicted Uncertainty. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198820802.003.0010.

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The chapter analyses the way in which structured finance manages and controls the openness of the future as a source of profit. Financial modelling relies on a specific form of fiction, based on the careful construction of a present image of the future and its uncertainty—expressed by the evaluation of implied volatility. The problem with this approach is that it fails to take account of the reflexive way in which the fictitious future it constructs affects the (not-yet-existing) future reality. This chapter highlights the dual nature of the future as intersection and combination of both the present future and the future present. It concludes that structured-financed models—despite their attempt to control risk by making calculations in the present about the future and about current market expectations of the future—may, in times of turbulence, increase the indeterminacy and unpredictability of future reality.
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Vickers, Brendan, i Sangeeta Khorana, red. Navigating Uncertainty. Commonwealth, 2018. http://dx.doi.org/10.14217/d302190b-en.

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50

Measurement Uncertainty. Boston, MA: Springer US, 2007. http://dx.doi.org/10.1007/978-0-387-46328-5.

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