000			03251nam a22003854u 4500
001			10.1002/9781394319060
003			Wiley
005			20251030120310.0
007			cr nn 008mam|a
008			241122t2024||||xxu fs| |0|| 0|eng||
020			_a9781394319060 _qelectronic
024	7		_a10.1002/9781394319060 _2doi
041			_aeng
100	1		_aKrzysztofowicz, Roman _4aut _991722
245	1	0	_aProbabilistic Forecasts and Optimal Decisions _h[electronic resource] _cRoman Krzysztofowicz
250			_a1
260			_bWiley _c2024
264		1	_bWiley _c2024
300			_a576pp.;
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _2rdaft
347			_bPDF
520			_aAccount for uncertainties and optimize decision-making with this thorough exposition Decision theory is a body of thought and research seeking to apply a mathematical-logical framework to assessing probability and optimizing decision-making. It has developed robust tools for addressing all major challenges to decision making. Yet the number of variables and uncertainties affecting each decision outcome, many of them beyond the decider's control, mean that decision-making is far from a 'solved problem'. The tools created by decision theory remain to be refined and applied to decisions in which uncertainties are prominent. Probabilistic Forecasts and Optimal Decisions introduces a theoretically-grounded methodology for optimizing decision-making under conditions of uncertainty. Beginning with an overview of the basic elements of probability theory and methods for modeling continuous variates, it proceeds to survey the mathematics of both continuous and discrete models, supporting each with key examples. The result is a crucial window into the complex but enormously rewarding world of decision theory. Readers of Probablistic Forecasts and Optimal Decisions will also find: Extended case studies supported with real-world data Mini-projects running through multiple chapters to illustrate different stages of the decision-making process End of chapter exercises designed to facilitate student learning Probabilistic Forecasts and Optimal Decisions is ideal for advanced undergraduate and graduate students in the sciences and engineering, as well as predictive analytics and decision analytics professionals.
650		4	_aSystems Engineering & Management
650		4	_aEngineering Technology Management _991588
650		4	_aApplied Mathematics in Engineering _991554
653	0	0	_aProbabilistic reasoning; statistical estimation; judgmental assessment; rational decision-making; discrete modeling; continuous modeling; decision theory; mathematical-logical analysis; uncertainty; discrete-event systems; decision analysis
776	0	8	_iPrinted edition: _z9781394221868
856	4	0	_uhttps://doi.org/10.1002/9781394319060 _aWiley Online Library
856	4	0	_uhttps://onlinelibrary.wiley.com/action/showBook?doi=10.1002%2F9781394319060 _aWiley Online Library
856	4	2	_3Cover Image _uhttps://onlinelibrary.wiley.com/cms/asset/15d0384b-ed29-4678-b573-89a4378d62b4/9781394319060.cover.gif _aWiley Online Library
999			_c67058 _d67058