EAD-5853 Aula 05 Capítulo 02 M&C + Psicologia Evolucionária

Apresentação em tema: "EAD-5853 Aula 05 Capítulo 02 M&C + Psicologia Evolucionária"— Transcrição da apresentação:

1 EAD-5853 Aula 05 Capítulo 02 M&C + Psicologia Evolucionária
Abraham Yu Natália & Vivi EAD-FEA

2 M&C Chapter 2 Uncertainty and Probability
A qualitative discussion on uncertainty: Chapter 7 – Uncertainty (Hammond, Keeney and Raiffa, 1999) M&C Chapter 1: Introduction M&C Chapter 2: “we concentrate on describing and communicating about uncertainty” M&C Chapter 10: review of probability theory FEA/USP EAD-5853 Abraham Yu

3 Hammond, Keeney e Raiffa
McNamee & Celona Definir o problema certo Especificar seus objetivos Criar alternativas imaginativas Entender as consequências Lançar mão de todas as suas escolhas (grapple with your trade-offs) Esclarecer suas incertezas Pensar muito sobre sua tolerância ao risco Considerar decisões interligadas 1. Definição apropriada do problema (framing) 2. Alternativas criativas e viáveis 3. Informação relevante e confiável 4. Valores e “trade-off” claros 5. Raciocínio lógico 6. Compromisso para a ação FEA/USP EAD-5853 Abraham Yu

4 Incertezas na Decisão: HK&R 07
In the preceding chapters, we’ve laid out a comprehensive approach to making smart choices when …you can know the consequences of each alternative before deciding We now turn to situations in which no matter how much time and thought you expend you won't know what the consequences will be until after deciding When you choose, you may know what might happen, but you won't know what will happen. EAD-5853 A. Yu

5 HK&R 07: Como Lidar com Incerteza?
You can't snap your fingers and make the uncertainties go away. But you can raise the odds of making a good decision in uncertain situations. How? The first step is to acknowledge the existence of the uncertainties. Then you need to think them through systematically, understanding the various outcomes that might unfold, their likelihoods, and their impacts. EAD-5853 A. Yu

6 HK&R 07: Distinguish Smart Choices from Good Consequences
Whenever uncertainty exists, there can be no guarantee that a smart choice will lead to good consequences. Although many people judge the quality of their own and others' decisions by the quality of the consequences - by how things turn out - this is an erroneous view. EAD-5853 A. Yu

7 HK&R 07: Use Risk Profiles to Simplify Decisions Involving Uncertainty
What are the key uncertainties? When there are many possible uncertainties, winnow them down to the few that are likely to matter most What are the possible outcomes of these uncertainties? Mutually exclusive, collectively exhaustive, unambiguously defined What are the chances of occurrence of each possible outcome? Assigning chances can be one of the toughest and most nerve-wracking tasks in decision making What are the consequences of each outcome? EAD-5853 A. Yu

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9 M&C Chapter 2 Uncertainty and Probability
Probability: a language of uncertainty Influence diagram (theory in Chapter 11) Why bother with probabilities? People claim that they deal adequately with uncertainty through the ordinary use of language What are probabilities The “divide and conquer” approach Clairvoyance test Assigning the numbers Distribution tree & probability tree Analyzing the tree Cumulative probability plot Histogram How much detail is enough? Certain equivalent and expected value Encoding probabilities (techniques in Chapter 12) FEA/USP EAD-5853 Abraham Yu

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14 Demanda por Fio Dental Um investimento de uma multinacional depende de uma estimativa da demanda brasileira de fio dental em 2018 Utilizando conhecimento da classe Sem acesso a outras fontes de informações Dados subjetivos – opiniões e julgamentos Primeiro passo - definir a medida da demanda A. Yu

15 Diagrama de Influencia
Identificar os fatores relevantes ao problema Círculos ou ovais Definir o significado de cada fator Medição Estabelecer as relações entre os fatores Setas ou influencias Desenvolvido para Marinha dos EUA (~1980) A. Yu

16 Estimar Probabilidade Subjetivamente
Definir bem o evento ou a variável preço do algodão Motivar o decisor / expert Identificar e anular vieses cognitivos fontes de informação cenários extremos Técnicas de codificação de probabilidade M&C Chapter 12 – Encoding a probability distribution A. Yu

17 Significado da “Influencia”
Causa – efeito? Dependência probabilística? P (X|Y) = P (X) Sequência cronológica? Relevância? Y X Abraham Yu EAD-5853

18 How Much Detail is Enough?
“a model adequate to make a choice” x “a good model of reality” Requisite decision models: “A model can be considered requisite only when no new intuitions emerge about the problem” Phillips, LD (1982) “Requisite decision modelling.” Journal of the Operational Research Society, 33,

19 Exercícios para Próxima Aula
M&C 2.5 M&C 2.7 M&C 2.9 M&C 2.12

20 Trabalho da Disciplina
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