L23/24: Introduction to Engineering Decision Making Flashcards
Two types of uncertainty
- aleatory uncertainty
- epistemic uncertainty
What is aleatory uncertainty?
natural randomness in the phenomena we are dealing with
What is epistemic uncertainty?
inaccuracy in our understanding and our models for prediciting reality
Basic options for making decisions based on incomplete knowledge and information.
- ignore the uncertainty (work with best point estimates)
- allow for uncertainty using intution (or engeering judement)
- adopt a scientific approach (use probabiliy and statistical analysis)
How to evaluate a solution to assess how well it has worked?
- has a change in the design approach or procurement process led to a decrease or increase in failures
- has changing the process for producing a material resulted in a better or worse material
Why are some people reluctant to concede there is uncertainty?
- “politics of uncertainty”, might be perceived as bein inconsistent with being an expert
Type 1 error:
Accused is not guilty but is concluded as guilty
Type 2 error:
Accused is guilty but is found to be not guilty
What is the focus of risk management?
Making decisions in the face of uncertainty, which entails identifying probability and consequences of making wrong decisions.
What is the essence of Bayesian Decision Theory?
Using additional data to reduce the probability of making wrong decisions.
What is the “state of nature”?
The true value of the uncertain variable. It cannot be determined with absolute confidence.
How to handle the ‘state of nature’?
Apply a probability distribution for the state of nature then use statistical decision theory.
Prob. dist. may be estimated using engineering judgement. Additional information may be required in some cases.
Notes on Decision Trees
- can have any number of actions and states; as this increases the decision tree gets more dense
- if have finite number of states use probibility mass function to describe probabilities
- if have infinite number of states use probability density function to describe probabilities
A decision is sensitive if:
- one test is done and the decision is different for different test results
- more than one test is done and the decision changes as new test results come to hand and the probability distribution for the state of nature are updated.
(sensitivity decreases as the number of tests increases.
Aim of doing tests:
- to obtain better information on the state of nature to assist making a decision
Result of doing a test
- might give a posterior probability distribution which exhibits less variance or uncertainty
may not change the decision
When to use preposterior analysis?
Where there are several possible tests, to identify which test (if any) should be done.
- before posterior analysis
Preposterior Analysis involves:
- updating the probability distribution for the state of nature, and deciding on which action to take
- calculating posterior probabilities for the state of nature and then deciding which action to take (given an experiment has been done and the results are known)
- deciding whether an experiment should be done and which experiment
When should tests be done?
When the expected value of the information obtained from the experiment exceeds the cost of the test.