Welcome to NUSAP net
  

Robust knowledge for Sustainability

Tutorials
Post Normal Science
NUSAP
Participatory IA
Sensitivity Analysis
GLUE
Expert elicitation
Uncertainty Communication
Pluralistic uncert. management
Glossary


Sections
Reports, papers, ...
RIVM/MNP Uncertainty Guidance
Model quality checklist
Interactive tools
Pedigree matrices


Related websites
Post Normal Times
The Integrated Assessment Society
Precautionary Principle
Renewable Energy Master


Main Menu
Home
Reviews
Web Links
Downloads
Your Account
Top 10

Other Options
· Members List


  
Welcome to NUSAP net Glossary

[ A |  B |  C |  D |  E |  F |  G |  H |  I |  J |  K |  L |  M |  N |  O |  P |  Q |  R |  S ]
[ T |  U |  V |  W |  X |  Y |  Z |  1 |  2 |  3 |  4 |  5 |  6 |  7 |  8 |  9 |  0 ]


[ 1 ]
 
Terms Definitions
Behavioural variability
Bias A constant or systematic deviation as opposed to a random error. It appears as a persistent over- or under-estimation of the quantity measured, calculated or estimated. See also expert bias and value loading.
Bias: Anchoring Assessments are often unduly weighted toward the conventional value, or first value given, or to the findings of previous assessments in making an assessment. Thus, they are said to be 'anchored' to this value.
Bias: Availability his bias refers to the tendency to give too much weight to readily available data or recent experience (which may not be representative of the required data) in making assessments.
Bias: Coherence Events are considered more likely when many scenarios can be created that lead to the event, or if some scenarios are particularly coherent. Conversely, events are considered unlikely when scenarios can not be imagined. Thus, probabilities tend to be assigned more on the basis of one's ability to tell coherent stories than on the basis of intrinsic probability of occurrence.
Bias: Overconfidence Experts tend to over-estimate their ability to make quantitative judgements. This can sometimes be seen when an estimate of a quantity and its uncertainty are given, and it is retrospectively discovered that the true value of the quantity lies outside the interval. This is difficult for an individual to guard against; but a general awareness of the tendency can be important.
Bias: Representativeness This is the tendency to place more confidence in a single piece of information that is considered representative of a process than in a larger body of more generalized information.
Bias: Satisficing this refers to a common tendency to search through a limited number of familiar solution options and to pick from among them. Comprehensiveness is sacrificed for expediency in this case.
Bias: Unstated assumptions A subject's responses are typically conditional on various unstated assumptions. The effect of these assumptions is often to constrain the degree of uncertainty reflected in the resulting estimate of a quantity. Stating assumptions explicitly can help reflect more of a subject's total uncertainty.
Burden of proof The `burden of proof' sets the onus of responsibility in argumentation according to whether one must prove positive or negative attributes (innocence/guilt; presence/absence, etc.) about the issue in dispute. The burden of proof therefore sets out who is responsible for making a case. For example, burden of proof in environmental regulation may be set such that an activity will not be regulated or prohibited unless proof of harm can be made. Alternatively, the burden of proof may be set such that activities of a certain kind will be prohibited unless it can be proved that they will do no harm.
 
[ 1 ]

nusap.net