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== Specialized disciplines == {{main|List of fields of application of statistics}} Statistical techniques are used in a wide range of types of scientific and social research, including: [[biostatistics]], [[computational biology]], [[computational sociology]], [[network biology]], [[social science]], [[sociology]] and [[social research]]. Some fields of inquiry use applied statistics so extensively that they have [[specialized terminology]]. These disciplines include: {{Columns-list|colwidth=30em|* [[Actuarial science]] (assesses risk in the insurance and finance industries) * Applied information economics * [[Astrostatistics]] (statistical evaluation of astronomical data) * [[Biostatistics]] * [[Chemometrics]] (for analysis of data from [[chemistry]]) * [[Data mining]] (applying statistics and [[pattern recognition]] to discover knowledge from data) * [[Data science]] * [[Demography]] (statistical study of populations) * [[Econometrics]] (statistical analysis of economic data) * [[Statistical study of energy data|Energy statistics]] * [[Engineering statistics]] * [[Epidemiology]] (statistical analysis of disease) * [[Geography]] and [[geographic information system]]s, specifically in [[spatial analysis]] * [[Image processing]] * [[Jurimetrics]] ([[law]]) * [[Medical statistics]] * [[Political science]] * [[Psychological statistics]] * [[Reliability engineering]] * [[Social statistics]] * [[Statistical mechanics]]}} In addition, there are particular types of statistical analysis that have also developed their own specialised terminology and methodology: {{Columns-list|colwidth=30em| * [[Bootstrapping (statistics)|Bootstrap]]{{\}}[[jackknife resampling]] * [[Multivariate statistics]] * [[Statistical classification]] * [[Structured data analysis (statistics)|Structured data analysis]] * [[Structural equation modelling]] * [[Survey methodology]] * [[Survival analysis]] * Statistics in various sports, particularly [[Baseball statistics|baseball]] β known as [[sabermetrics]] β and [[Cricket statistics|cricket]] }} Statistics form a key basis tool in business and manufacturing as well. It is used to understand measurement systems variability, control processes (as in [[statistical process control]] or SPC), for summarizing data, and to make data-driven decisions.
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