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: http://zebu.uoregon.edu/2004/es399/lec01.html
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Define some environmental problem.
Step 1: Tabulate the set of emotional and passionate responses and viewpoints that exist on the problem. These viewpoints can be irrational.
In the real world, progress beyond this step is rarely achieved and different groups just end up arguing over various irrational viewpoints, none of which can be supported.
However, to be effective in this arena, one has to be aware that such
irrational viewpoints exist and to develop methods and tactics to
diffuse them.
Step 2: Design experiments of data acquisition techniques that can
actually address the individual issues raised above. Most of the
group exercises will be devoted to this critical step.
Step 3: Perform unbiased data analysis and go where the data leads,
instead of using the data to support a cherished notion or personal
prejudice.
Step 4: Develop policies and solution spaces based on premises that can be
defended and are consistent with the available data.
Beware of three main problems with Environmental Data:
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Elementary Data Analysis:
The first steps are to produce a distribution (histogram) of the variables and define the statistical components of that distribution (usually just the mean and the standard deviation.
After doing that one wants to attempt a simple linear regression to search for correlation in the data.
Benefits of Linear Regression: