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E-217-PROG-2010-1: Simulation 1 Thorisson Lecture Notes

Concepts

Simulation A model of a process that can transform an initial state to a future state
Scientific Method In Western science, the usage of a set of principles that facilitate the production of reliable knowledge
Theory (isl. kenning) “A set of statements or principles devised to explain a group of facts or phenomena, especially one that has been repeatedly tested or is widely accepted and can be used to make predictions about natural phenomena.” REF
A theory is a relatively big explanation, covering several phenomena, often through a single principle, or a set of simple principles.
Hypothesis (isl. tilgáta) Is a prediction about the relationship between a limited set of phenomena, as explained by a particular theory
Experimental design “A planned interference in the natural order of events“
Sample: Subject selection from a “population” A representative subset, drawn from a population, of the phenomenon we are studying.

Examples:
a. Siggi, Maggi and Biggi representing human males.
b. 10 lakes representing all freshwater on the Earth's surface.
c. rust on bottom of doors representing the overall state of an automobile.
A sample should be randomly chosen to (1) minimize spurious correlations and thus (2) maximize the generalizability of the results of measuring only a small subset of the phenomenon. |

Sample Distribution
Data Typically “raw numbers” – only contain low-level semantics
Information Processed and prepared data
Statistics Mathematical methods for dealing with uncertainty





The Scientific Method: Classical Description

Identification, description and formalization of phenomenon 1. Observation and description of a phenomenon or group of phenomena.
Hypothesis, null-hypothesis 2. Formulation of an hypothesis to explain the phenomena. In physics, the hypothesis often takes the form of a causal mechanism or a mathematical relation.
Creation of experimental setup to test hypothesis 3. Use of the hypothesis to predict the existence of other phenomena, or to predict quantitatively the results of new observations.
Performance of experiment, collection and analysis of results 4. Performance of experimental tests of the predictions by several independent experimenters and properly performed experiments. Basic assumption: Repeatability — Can be repeated by anyone anywhere
Repeatability requires formal framework Detailed description, clear goals, clear (limited) scope, hence the formalities in their execution
Key idea: Comparsion Baseline collected in same experimental setup without any other intervention by experimenter





Where Simulation Fits In

“Connecting Glue” Bridges between real-world experimentation, theory and hypotheses
More flexible than real-world experiments
Less reliable than real-world experiments





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