Applied Statistics
Statistics refers to the scientific discipline of data collection, organization and
interpretation, which includes the data collection planning to be used in surveys and
experiments, and is also considered a distinct mathematical science. The field uses
data and statistical models to enable forecasting in such areas as the natural and social
sciences, government, business and sports. Descriptive statistics refers to the summary
of a collection of data that can be used in research, including the modeling of data in a
way that would indicate randomness in observations. Inferential statistics refers to the
use of such random observations to draw inferences on the studied population.[1]
Statisticians are specialists in applying statistical analysis. They design experiments and
conduct survey sampling to improve data quality and can help various organizations
without having access to knowledge relevant to their specific problems.[2]
Applied statistics refers both to the work of professional statisticians who produce and
present statistics and to statistical interpretation as performed by statisticians, by
statistical users and by the general public. It often use statistics theory to provide a
ready source of information and has contributed significantly to scientific research.
However, applied statistics has also been a source of misinformation, such as in the
statistical misinterpretation by some in the medical, legal and financial professions that
have led to erroneous diagnoses, imprisonment and financial risk assessments.[3]
Statistics are numerical observations of facts and therefore fallible. Their reliability
depend on the representability and accuracy of the observed facts and their correct
interpretation. It is also important to appreciate the methods by which statistics are
generated. A controlled experiment is the easiest method to use because disturbing
influences can be minimized, while the design of experiments range of methodologies,
including its associated software packages, is used when there are lesser degrees of
control. Sources of error in taking samples include the variable results every time a
sample is taken and the difference in the qualities of the sample from the population it
intends to represent. Most published and unpublished statistics contain elements of
subjectivity, which is why their objectivity is usually subject to review by an independent
body. The reliability of published statistics are usually only available when a variable is
is obtained from multiple sources or when revisions are made, as in the differences
between victim-reported and police-reported crime rates.[4]
Some statistical findings can be successfully interpreted verbally and by a mixture of
verbal logic and the rules of chance. Their successful use involves the combining of
available tools of inference with their safe application to a particular problem.
Managers of such work have the responsibility of understanding statistical concepts,
including their limitations, before making a decision based on them.[5]
The quantification of intuitive significance and confidence that would allow objective
answers on questions like how likely is it or how confident are we in relation to a certain
subject are major contributions of statistics theory. Statistical correlation can also be
used to explore a connection when the possible errors in the available evidence are
attributable only to chance.[6]
The human brain’s making of intuitive probability judgments is usually erroneous even
if it is fairly right in intuitive judgments such as those involving speed or distance. The
use of heuristics instead of analysis causes distortion in numerical data interpretation,
such as in the overestimation of bigger events like rail disasters and the
underestimation of smaller events like road accidents. Statistical errors such as
misinterpreting non-significant findings as significant have occurred in medical research
reports in two respected medical journals. Survivor bias has been used by financial
analysts to statistically mislead potential clients to show the benefits that would have
been obtained if investments had previously been made in their currently recommended
portfolio.[7]
[1] “Statistics”, Wikipedia, 4 May 2011, <http://en.wikipedia.org/wiki/Statistics> [accessed 9 May 2011]
[2] ibid
[3] “Applied Statistics”, Citizendium, 17 February 2011, <http://en.citizendium.org/wiki/Applied_statistics>
[accessed 9 May 2011]
[4] ibid
[5] ibid
[6] ibid
[7] ibid
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