Editing Social statistics (section)

==Statistics in the social sciences==
===History===

[[File:Statue élevée à la mémoire de Adolphe Quetelet.jpg|thumb|right|upright=1.05|[[Adolph Quetelet]] published data on European population.]]

[[Adolph Quetelet]] was a proponent of [[social physics]]. In his book ''Physique sociale''<ref>A. Quetelet, Physique Sociale, https://archive.org/details/physiquesociale00quetgoog</ref> he presents distributions of human [[height]]s, [[age of marriage]], time of birth and death, [[time series]] of human marriages, births and deaths, a [[survival function|survival density]] for humans and curve describing [[fecundity]] as a function of age. He also developed the [[Quetelet Index]].

[[Francis Ysidro Edgeworth]] published "On Methods of Ascertaining Variations in the Rate of Births, Deaths, and Marriages" in 1885<ref>{{cite journal|first=F. Y.|last=Edgeworth |title=On Methods of Ascertaining Variations in the Rate of Births, Deaths, and Marriages|journal=[[Journal of the Statistical Society of London]] |year=1885 |volume=48 |issue=4 |pages=628–649 |jstor=2979201 |doi=10.2307/2979201}}</ref> which uses squares of differences for studying fluctuations and [[George Udny Yule]] published "On the [[Correlation]] of total [[Pauperism]] with Proportion of [[Poor relief|Out-Relief]]" in 1895.<ref>{{cite journal|first=G. U.|last=Yule |title=On the Correlation of total Pauperism with Proportion of Out-Relief|journal=[[The Economic Journal]] |year=1895 |volume=5 |issue=20 |pages=603–611|jstor=2956650 |doi=10.2307/2956650}}</ref>

A numerical [[calibration (statistics)|calibration]] for the fertility curve was given by [[Karl Pearson]] in 1897 in his "The Chances of Death, and Other Studies in Evolution"<ref>K. Pearson, The Chances of Death, and Other Studies in Evolution, 1897 https://archive.org/details/chancesdeathand00peargoog</ref> In this book Pearson also uses [[standard deviation]], [[correlation]] and [[skewness]] for studying humans.

[[Vilfredo Pareto]] published his analysis of the [[distribution of income]] in [[Great Britain]] and [[Ireland]] in 1897,<ref>V. Pareto, Cours d'Économie Politique, vol. II, 1897</ref> this is now known as the [[Pareto principle]].

[[Louis Guttman]] proposed that the values of [[ordinal variable]]s can be represented by a [[Guttman scale]], which is useful if the number of variables is large and allows the use of techniques such as [[ordinary least squares]].<ref>{{cite journal|first=L.|last=Guttman |title=A Basis for Scaling Qualitative Data|journal=[[American Sociological Review]] |year=1944 |volume=9 |issue=20 |pages=603–611|doi=10.2307/2086306 |jstor=2086306}}</ref>

[[Macroeconomic]] statistical research has provided [[stylized facts]], which include:
* [[Bowley's law]] (1937) regarding the proportion between [[wages]] and national output <ref>A. Bowley, Wages and income in the United kingdom since 1860, 1937</ref>
* The [[Phillips curve]] (1958) regarding the relation between [[wages]] and [[unemployment]]<ref>W. Phillips, The Relation Between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957, published 1958</ref>

Statistics and statistical analyses have become a key feature of social science: statistics is employed in [[economics]], [[psychology]], [[political science]], [[sociology]] and [[anthropology]].

=== Statistical methods in social sciences===
[[File:Path example.JPG|thumb|right|upright=1.05|Diagram illustrating [[path analysis (statistics)|path analysis]]: causal paths link endogenous variables and exogenous variables.]]
[[File:SLINK-density-data.svg|thumb|right|upright=1.05|[[Cluster analysis]] showing two main clusters]]
[[File:Perceptron cant choose.svg|thumb|right|upright=1.05|A classification performed using the [[perceptron]] algorithm]]

Methods and concepts used in quantitative social sciences include:<ref name="MilSal">{{citation |year=2002 |author=Miller, Delbert C., & Salkind, Neil J |title=Handbook of Research Design and Social Measurement |place=California |publisher=Sage |isbn=0-7619-2046-3 |url=https://books.google.com/books?id=sgoHv5ZP6dcC&q=measurement+social}}</ref>
* [[Research design]], [[survey methodology]] and [[survey sampling]]
* [[Delphi method]]

Statistical techniques include:<ref name="MilSal"/>

====Covariance based methods====

* [[Regression analysis]]
* [[Canonical correlation]]
* [[Causal analysis]]
* [[Multilevel models]]
* [[Factor analysis]]
* [[Linear discriminant analysis]]
* [[Path analysis (statistics)|Path analysis]]
* [[Structural Equation Modeling]]

====Probability based methods====

* [[Probit]] and [[logit]]
* [[Item response theory]]
* [[Bayesian statistics]]
* [[Stochastic process]]
* [[Latent class model]]

====Distance based methods====

* [[Cluster analysis]]
* [[Multidimensional scaling]]

====Methods for categorical data====

* [[Classification analysis]]
* [[Cohort analysis]]

=== Usage and applications{{anchor|Applications}} ===

Social scientists use social statistics for many purposes, including:
* the [[program evaluation|evaluation]] of the quality of [[Service (economics)|service]]s available to a group or organization,
* analyzing behaviors of groups of people in their environment and special situations,
* determining the wants of people through statistical [[Sampling (statistics)|sampling]]
* evaluation of wage expenditures and savings<ref name="Hoffman">{{cite journal |last1=Hoffman |first1=Frederick |title=Problems of Social Statistics and Social Research |journal=Publications of the American Statistical Association |date=1908 |volume=11 |issue=82|pages=105–132 |doi=10.2307/2276101 |jstor=2276101 }}</ref>
* preventing industrial diseases<ref name="Hoffman"/>
* prevention of industrial accidents<ref name="Hoffman"/>
* [[labour dispute]]s, such as supporting the [[Coal strike of 1902|Anthracite Coal Strike Commission of 1902-1903]]<ref>{{cite journal |last1=Willcox |first1=Walter |title=The Need of Social Statistics as an Aid to the Courts |journal=Publications of the American Statistical Association |date=1908 |volume=13 |issue=82}}</ref>
* supporting governments in times of peace and war<ref>{{cite journal |last1=Mitchell |first1=Wesley |title=Statistics and Government |journal=Publications of the American Statistical Association |date=1919 |volume=16 |issue=125|pages=223–235 |doi=10.2307/2965000 |jstor=2965000 }}</ref>

===Reliability===

The use of statistics has become so widespread in the social sciences that many universities such as [[Harvard]], have developed institutes focusing on "quantitative social science." Harvard's Institute for Quantitative Social Science focuses mainly on fields like [[political science]] that incorporate the advanced causal statistical models that [[Bayesian method]]s provide. However, some experts in causality feel that these claims of [[causal analysis|causal statistics]] are overstated.<ref>[[Judea Pearl|Pearl, Judea]] 2001, Bayesianism and Causality, or, Why I am only a Half-Bayesian, Foundations of Bayesianism, Kluwer Applied Logic Series, Kluwer Academic Publishers, Vol 24, D. Cornfield and J. Williamson (Eds.) 19-36.</ref><ref>J. Pearl, Bayesianism and causality, or, why I am only a half-bayesian http://ftp.cs.ucla.edu/pub/stat_ser/r284-reprint.pdf</ref> There is a debate regarding the uses and value of statistical methods in social science, especially in [[political science]], with some statisticians questioning practices such as [[data dredging]] that can lead to  unreliable policy conclusions of political partisans who overestimate the interpretive power that non-robust statistical methods such as simple and multiple [[linear regression]] allow. Indeed, an important axiom that social scientists cite, but often forget, is that "[[correlation does not imply causation]]."