addressing uncertainty in oil and natural gas industry greenhouse

Appendix A
GLOSSARY OF STATISTICAL AND GHG INVENTORY TERMS, continued
TERM STATISTICAL DEFINITION GHG INVENTORY APPLICATION
RANDOM ERROR The difference between an individual
measurement and the limiting value of the
sample mean.
An error that varies in an unpredictable
manner when a large number of
measurements of the same variable are
made under effectively identical
conditions.
RANDOM SAMPLE
RANDOM
VARIABLE
RANGE
REPEATABILITY
A sample of n items chosen from a
population such that every possible sample
has the same probability of being chosen.
A variable that may take any of the values
of a specified set of values that are
represented by a probability distribution.
Region between the limits within which a
quantity is measured.
A measure of the agreement between the
results of successive measurements of the
same variable carried out by the same
method, with the same instrument, at the
same location, and within a short period of
time.
REPRODUCIBILITY A measure of the agreement between the
results of measurements of the same
variable where individual measurements are
carried out by the same methods, with the
same type of instruments, but by different
observers at different locations, and after a
long period of time.
RESIDUAL
SAMPLE
SENSITIVITY
ANALYSIS
STANDARD
DEVIATION
STANDARD ERROR
OF THE MEAN
The difference between the observed value
and the value predicted by a statistical
model, e.g. by linear regression.
A sample is a finite set of observations
drawn from a population.
This is a study to determine how sensitive
(or stable) is a calculation method to
variations of its input data or underlying
assumptions.
The population standard deviation is the
positive square root of the variance. It is
estimated by the sample standard deviation
that is the positive square root of the sample
variance.
A term often used to signify the sample
standard deviation of the mean.
A ‘discrete’ random variable is one that
may take only isolated values.
A ‘continuous’ random variable is one
that may take any value within a finite
or infinite interval.
It is the component of an observation
that cannot be explained by the model.
This analysis can include observing the
range of output values that correspond
to input variables; and calculating finite
difference approximations for studying
error propagation within a system.
Pilot Version, September 2009 A-5