Software

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Software
Modelling Data Variability
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• 1GS314 RISK ANALYSIS ASSESSMENT

SCHOOL OF EARTH ENVIRONMENTAL
SCIENCES Practical 1 Bestfit (Granite Data)
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The Modelling Process
Data
FOS
Need to Describe VARIABILITY
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Model Equation
Monte Carlo Simulation
Statistics Distributions Fit a Variety
QRA
Test Goodness of Fit
Expert Judgement
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Software
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Granite Data
174 151 176 186 187 185 171 178 189 135 197 201 15
0 179 181 177 205 195 196 191 201
Geological Issues?
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Enter Data
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Distribution Specification
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Distribution Specification
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Run Fit Results Presented
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Run Fit Results Presented
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Run Fit Results Presented
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Comparison Graph
INPUT DATA
Comparison Graphs Input and result distributions
are superimposed on the same graph. Allows you to
determine whether the best fit distribution is
well matched to the input data in specific areas.
i.e. it may be important to have a good match
around the mean or in the tails.
FITTED MODEL
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Run Fit Results Presented
Statistical Distribution to Describe Variability i
n Data
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Difference Graph
Difference Graphs The difference graph displays
the absolute error between the input and results
distributions. This error is defined as the
difference between the input and results
probability for each input value of x. Comparing
the magnitude of the error to the magnitude of
the result gives an idea of the extent to which
the results deviate from the input.
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P P Graph
P-P Graphs Probability-Probability (P-P) graphs
plot the distribution of the input data versus
the distribution of the results. If the fit is
good the plot will be nearly linear.
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Q Q Graph
Q-Q Graphs Quantile-Quantile (Q-Q) graphs plot
the percentile values of the input distribution
versus percentile values of the results. If the
fit is good the plot will be nearly linear.
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Populations?
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135 MPa deleted
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151 MPa 150 MPa deleted
Uniform Distribution Bounded Between 169MPa
207Mpa
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Difference Graph
Is this better ?
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P P Graph
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Q Q Graph
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?
Original
Edited
Answer or Aid to Decision Making?
JUDGEMENT
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The Expert ?