A
fresh Saturday morning started with a relatively odd topic, discussion on
Mughal's history, though I strongly believe that they too can contribute to
this blog on analysis but not today. The thought of our history kept rolling in
my mind and I sat down to search on history of what I do, statistics.
With
great efforts on www.google.com I got about 1,690,000,000 results (0.18
seconds), thought it will be good to mention as I am writing about statistics.
The very first link was from among the most trusted and read online free
encyclopedia www.wikipedia.org
.
Though
there is a lot which is written on the link (given at the end), I thought a
part of it should be shared, especially the origin, meaning and current
statistics.
The
history of statistics can be said to start around 1749 although, over
time, there have been changes to the interpretation of what the word statistics
means. In early times, the meaning was restricted to information about states.
This was later extended to include all collections of information of all types,
and later still it was extended to include the analysis and interpretation of
such data. In modern terms, "statistics" means both sets of collected
information, as in national accounts and temperature records, and analytical
work which require statistical inference.
Statistical
activities are often associated with models expressed using probabilities, and
require probability theory for them to be put on a firm theoretical basis.
A
number of statistical concepts have had an important impact on a wide range of
sciences. These include the design of experiments and approaches to statistical
inference such as Bayesian inference, each of which can be considered to have
their own sequence in the development of the ideas underlying modern
statistics.
Introduction
By
the 18th century, the term "statistics" designated the systematic
collection of demographic and economic data by states. In the early 19th
century, the meaning of "statistics" broadened, then including the
discipline concerned with the collection, summary, and analysis of data. Today
statistics is widely employed in government, business, and all the sciences.
Electronic computers have expedited statistical computation, and have allowed
statisticians to develop "computer-intensive" methods.
The
term "mathematical statistics" designates the mathematical theories
of probability and statistical inference, which are used in statistical
practice. The relation between statistics and probability theory developed
rather late, however. In the 19th century, statistics increasingly used
probability theory, whose initial results were found in the 17th and 18th
centuries, particularly in the analysis of games of chance (gambling). By 1800,
astronomy used probability models and statistical theories, particularly the
method of least squares, which was invented by Legendre and Gauss. Early
probability theory and statistics was systematized and extended by Laplace;
following Laplace, probability and statistics have been in continual
development. In the 19th century, social scientists used statistical reasoning
and probability models to advance the new sciences of experimental psychology
and sociology; physical scientists used statistical reasoning and probability models
to advance the new sciences of thermodynamics and statistical mechanics. The
development of statistical reasoning was closely associated with the
development of inductive logic and the scientific method.
Statistics
is not a field of mathematics but an autonomous mathematical science, like
computer science or operations research. Unlike mathematics, statistics had its
origins in public administration and maintains a special concern with
demography and economics. Being concerned with the scientific method and
inductive logic, statistical theory has close association with the philosophy
of science; with its emphasis on learning from data and making best
predictions, statistics has great overlap with the decision science and
microeconomics. With its concerns with data, statistics has overlap with
information science and computer science.
Etymology
The term statistics is ultimately derived from the New Latin statisticum collegium ("council of state") and the Italian word statista ("statesman" or "politician"). The German Statistik, first introduced by Gottfried Achenwall (1749), originally designated the analysis of data about the state, signifying the "science of state" (then called political arithmetic in English). It acquired the meaning of the collection and classification of data generally in the early 19th century. It was introduced into English in 1791 by Sir John Sinclair when he published the first of 21 volumes titled Statistical Account of Scotland.
Thus, the original principal purpose of Statistik was data to be used by governmental and (often centralized) administrative bodies. The collection of data about states and localities continues, largely through national and international statistical services. In particular, censuses provide regular information about the population.
The first book to have 'statistics' in its title was "Contributions to Vital Statistics" by Francis GP Neison, actuary to the Medical Invalid and General Life Office (1st ed., 1845; 2nd ed., 1846; 3rd ed., 1857).
Statistics Today
During the 20th century, the creation of precise instruments for agricultural research, public health concerns (epidemirology, biostatistics, etc.), industrial quality control, and economic and social purposes (unemployment rate, econometry, etc.) necessitated substantial advances in statistical practices.
Today the use of statistics has broadened far beyond its origins. Individuals and organizations use statistics to understand data and make informed decisions throughout the natural and social sciences, medicine, business, and other areas.
Statistics is generally regarded not as a subfield of mathematics but rather as a distinct, albeit allied, field. Many universities maintain separate mathematics and statistics departments. Statistics is also taught in departments as diverse as psychology, education, and public health.
Also see for scope of statistical applications: http://numberstory.blogspot.in/2010/12/number-story.html
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