Analyzing data using Python - Risk Engineering
[Pages:53]Analyzing data using Python
Eric Marsden
The purpose of computing is insight, not numbers. ? Richard Hamming
Where does this fit into risk engineering?
curve
fitting
data
probabilistic model
consequence model
event probabilities
event consequences
risks
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Where does this fit into risk engineering?
curve
fitting
data
probabilistic model
consequence model
event probabilities
event consequences
risks
costs
criteria
decision-making
2 / 49
Where does this fit into risk engineering?
curve
fitting
data
probabilistic model
consequence model
These slides
2 / 49
event probabilities
event consequences
risks
costs
criteria
decision-making
Descriptive statistics
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Descriptive statistics
Descriptive statistics allow you to summarize information about observations ? organize and simplify data to help understand it
Inferential statistics use observations (data from a sample) to make inferences about the total population ? generalize from a sample to a population
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Descriptive statistics
Source: 5 / 49
Measures of central tendency
Central tendency (the "middle" of your data) is measured either by the median or the mean
The median is the point in the distribution where half the values are lower, and half higher ? it's the 0.5 quantile
The (arithmetic) mean (also called the average or the mathematical expectation) is the "center of mass" of the distribution ? continuous case: () = () ? discrete case: () = ()
The mode is the element that occurs most frequently in your data
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