12
Chapter 2: Misuses
data be created - with the problem that these data are describing the
real climate system only to some unknown extent.
• Almost all data in climate research are interrelated both in space and
time - this spatial and temporal correlation is most useful since it allows the reconstruction of the space-time state of the atmosphere and
the ocean from a limited number of observations. However, for statistical inference, i.e., the process of inferring from a limited sampie robust
statements about an hypothetical underlying "true" structure, this correlation causes difficulties since most standard statistical techniques use
the basic premise that the data are derived in independent experiments.
Because of these two problems the fundamental question of how much
information about the examined process is really available can often hardly
be answered. Confusion about the amount of information is an excellent
hotbed for methodological insufliciencies and even outright errors. Many
such insufliciencies and errors arise from
• The obsession with statistical recipes in particular hypothesis testing.
Some people, and sometimes even peer reviewers, react like Pawlow's
dogs when they see a hypothesis derived from data and they demand a
statistical test of the hypothesis. (See Section 2.2.)
• The use of statistical techniques as a cook-book like recipe without a
real understanding about the concepts and the limitation arising from
unavoidable basic assumptions. Often these basic assumptions are disregarded with the effect that the conclusion of the statistical analysis
is void. A standard example is disregard of the serial correlation. (See
Sections 2.3 and 9.4.)
• The misunderstanding of given names. Sometimes physically meaningful
names are attributed to mathematically defined objects. These objects,
for instance the Decorrelation Time, make perfeet sense when used as
prescribed. However, often the statistical definition is forgotten and the
physical meaning of the name is taken as adefinition of the object - which
is then interpreted in a different and sometimes inadequate manner. (See
Section 2.4.)
• The use of sophisticated techniques. It happens again and again that
some people expect miracle-like results from advanced techniques. The
results of such advanced, for a "layman" supposedly non-understandable,
techniques are then believed without further doubts. (See Section 2.5.)
Chapter 2: Misuses
data be created - with the problem that these data are describing the
real climate system only to some unknown extent.
• Almost all data in climate research are interrelated both in space and
time - this spatial and temporal correlation is most useful since it allows the reconstruction of the space-time state of the atmosphere and
the ocean from a limited number of observations. However, for statistical inference, i.e., the process of inferring from a limited sampie robust
statements about an hypothetical underlying "true" structure, this correlation causes difficulties since most standard statistical techniques use
the basic premise that the data are derived in independent experiments.
Because of these two problems the fundamental question of how much
information about the examined process is really available can often hardly
be answered. Confusion about the amount of information is an excellent
hotbed for methodological insufliciencies and even outright errors. Many
such insufliciencies and errors arise from
• The obsession with statistical recipes in particular hypothesis testing.
Some people, and sometimes even peer reviewers, react like Pawlow's
dogs when they see a hypothesis derived from data and they demand a
statistical test of the hypothesis. (See Section 2.2.)
• The use of statistical techniques as a cook-book like recipe without a
real understanding about the concepts and the limitation arising from
unavoidable basic assumptions. Often these basic assumptions are disregarded with the effect that the conclusion of the statistical analysis
is void. A standard example is disregard of the serial correlation. (See
Sections 2.3 and 9.4.)
• The misunderstanding of given names. Sometimes physically meaningful
names are attributed to mathematically defined objects. These objects,
for instance the Decorrelation Time, make perfeet sense when used as
prescribed. However, often the statistical definition is forgotten and the
physical meaning of the name is taken as adefinition of the object - which
is then interpreted in a different and sometimes inadequate manner. (See
Section 2.4.)
• The use of sophisticated techniques. It happens again and again that
some people expect miracle-like results from advanced techniques. The
results of such advanced, for a "layman" supposedly non-understandable,
techniques are then believed without further doubts. (See Section 2.5.)