PPT-Planning for Uncertainty

Duncan Green fp2p Oxfam March 2014 In development some systems are more or less linear But many are not So is Traditional Planning a good use of our time For Allocating Building common goals and approaches. Nick Bloom (Stanford & NBER). Harvard, April 23. rd. and 30. th. Talk summarizes . a forthcoming JEP article (& a work-in-progress longer JEL). Talk summarizes . a forthcoming JEP article (& a work-in-progress longer JEL). 24 of . 42. Planning:. Monitoring & . Replanning. ,. Continuous . Planning. William H. Hsu. Department of Computing and Information Sciences, KSU. KSOL course page: . http://snipurl.com/v9v3. Course web site: . Readings. Readings. Baye. 6. th. edition or 7. th. edition, Chapter 3. BA 445 Lesson A.4 Uncertainty. Overview. Overview. Overview. BA 445 Lesson A.4 Uncertainty. Expected Value . distinguishes good decisions from good luck. Gambling with positive expected value virtually guarantees . sources:. sensory/processing noise. ignorance. change. consequences:. inference. learning. coding:. distributional/probabilistic population codes. neuromodulators. Multisensory Integration. +.  . apply the previous analysis:. Rrs. ) and output ocean color data:. a brief review. Stéphane. . Maritorena. – ERI/UCSB. Uncertainties in output products. Ideally, the uncertainties associated with ocean color products should be determined through comparisons with in situ measurements (matchups). Nick Bloom (Stanford & NBER). Harvard, April 23. rd. and 30. th. Talk summarizes . a forthcoming JEP article (& a work-in-progress longer JEL). Talk summarizes . a forthcoming JEP article (& a work-in-progress longer JEL). . Avoidance. in 10 minutes. Geert Hofstede. January. 2015. Origin. of the term “. uncertainty. . avoidance. ”. One. of the . key. . concepts. in a “. behavioral. . theory. of the . firm. Turing Fellow at the Alan Turing Institute. Thanks to Amy Wilson, Stan Zachary, Michael Goldstein – and too many others to name. Statistical modelling for planning and policy applications. It matters!. 1Overviewe the operationalrisksand deter the investment and the hiring ofnew employees These will give the pressure on the macroeconomy like GDP growth unemployment rateetcRecentlyconsiderable uncerta A. KHINE. DIVISION OF CHEMICAL PATHOLOGY. NHLS TYGERBERG . STELLENBOSCH UNIVERSITY. Laboratory Management workshop 3-6 June 2019. MEASUREMENT UNCERTAINTY. is a parameter, associated with the result of a measurement… that defines the range of the values that could reasonably be attributed to the measured quantity (UKAS). Uncertainty Essentials. Les Coveney, INAB Calibration & Uncertainty Day, 18th June 2018. Les Coveney, INAB Calibration & Uncertainty Day, 18th June 2018. Uncertainty Essentials. Definition of Measurement Uncertainty. High-dimensional Data Analysis. Adel Javanmard. Stanford University. 1. What is . high. -dimensional data?. Modern data sets are both massive and fine-grained.. 2. # Features (variables) > . # . Observations (Samples). SMART. Planning and Rescoping charettes. Former Feasibility Study Process . Overly detailed, expensive & time-consuming.. Detailed data generation for multiple alternatives was not consistently leading to a better product or decision.. An Evaluation of Development Viability. Peter Byrne. Pat McAllister. Peter Wyatt. www.henley.reading.ac.uk/rep/fulltxt/0810.pdf. Structure. Main Research questions. Background and context. Current practice.