**Social statistics** is the use of statistical measurement systems to study human behavior in a social environment. This can be accomplished through polling a group of people, evaluating a subset of data obtained about a group of people, or by observation and statistical analysis of a set of data that relates to people and their behaviors.

Adolph Quetelet was a proponent of social physics. In his book Physique sociale^{ [1] } he presents distributions of human heights, age of marriage, time of birth and death, time series of human marriages, births and deaths, a 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^{ [2] } which uses squares of differences for studying fluctuations and George Udny Yule published "On the Correlation of total Pauperism with Proportion of Out-Relief " in 1895.^{ [3] }

A numerical calibration for the fertility curve was given by Karl Pearson in 1897 in his "The Chances of Death, and Other Studies in Evolution"^{ [4] } 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,^{ [5] } this is now known as the Pareto principle.

Louis Guttman proposed that the values of ordinal variables 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.^{ [6] }

Macroeconomic statistical research has provided stylized facts, which include:

- Bowley's law (1937) regarding the proportion between wages and national output
^{ [7] } - The Phillips curve (1958) regarding the relation between wages and unemployment
^{ [8] }

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

Methods and concepts used in quantitative social sciences include:^{ [9] }

Statistical techniques include:^{ [9] }

Social scientists use social statistics for many purposes, including:

- the evaluation of the quality of services 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
- evaluation of wage expenditures and savings
^{ [10] } - preventing industrial diseases
^{ [10] } - prevention of industrial accidents
^{ [10] } - labour disputes, such as supporting the Anthracite Coal Strike Commission of 1902-1903
^{ [11] } - supporting governments in times of peace and war
^{ [12] }

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 methods provide. However, some experts in causality feel that these claims of causal statistics are overstated.^{ [13] }^{ [14] } 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." For example, it appears widely accepted that the lower numbers of women in decision making positions in politics, business and science is good evidence of gender discrimination. But where men suffer adverse statistical indicators such as greater imprisonment rates or a higher suicide rate, that is not usually accepted as evidence of gender bias acting against them.

- Blalock, H.M. Jr, ed. (1974),
*Measurement in the Social Sciences*, Chicago, Illinois: Aldine Publishing, ISBN 0-202-30272-5 , retrieved 10 July 2010 - S. Kolenikov, D. Steinley, L. Thombs (2010),
*Statistics in the Social Sciences: Current Methodological Developments*, Wiley`{{citation}}`

: CS1 maint: multiple names: authors list (link) - Blalock, Hubert M (1979),
*Social Statistics*, New York: McGraw-Hill, ISBN 0-07-005752-4 - Irvine, John, Miles, Ian, Evans, Jeff, (editors), "Demystifying Social Statistics ", London : Pluto Press, 1979. ISBN 0-86104-069-4
- Miller, Delbert C., & Salkind, Neil J (2002),
*Handbook of Research Design and Social Measurement*, California: Sage, ISBN 0-7619-2046-3 , retrieved 10 July 2010`{{citation}}`

: CS1 maint: multiple names: authors list (link) - Dietz, Thomas, & Kalof, Linda (2009),
*Introduction to Social Statistics*, California: Wiley-Blackwell`{{citation}}`

: CS1 maint: multiple names: authors list (link)

**Econometrics** is the application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference". An introductory economics textbook describes econometrics as allowing economists "to sift through mountains of data to extract simple relationships". Jan Tinbergen is one of the two founding fathers of econometrics. The other, Ragnar Frisch, also coined the term in the sense in which it is used today.

**Psychological statistics** is application of formulas, theorems, numbers and laws to psychology. Statistical methods for psychology include development and application statistical theory and methods for modeling psychological data. These methods include psychometrics, factor analysis, experimental designs, and Bayesian statistics. The article also discusses journals in the same field.

**Statistics** is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments.

A **case study** is an in-depth, detailed examination of a particular case within a real-world context. For example, case studies in medicine may focus on an individual patient or ailment; case studies in business might cover a particular firm's strategy or a broader market; similarly, case studies in politics can range from a narrow happening over time to an enormous undertaking.

**Quantitative research** is a research strategy that focuses on quantifying the collection and analysis of data. It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies.

In statistics, a **spurious relationship** or **spurious correlation** is a mathematical relationship in which two or more events or variables are associated but *not* causally related, due to either coincidence or the presence of a certain third, unseen factor.

In statistics, **path analysis** is used to describe the directed dependencies among a set of variables. This includes models equivalent to any form of multiple regression analysis, factor analysis, canonical correlation analysis, discriminant analysis, as well as more general families of models in the multivariate analysis of variance and covariance analyses.

**Structural equation modeling** (**SEM**) is a label for a diverse set of methods used by scientists in both experimental and observational research across the sciences, business, and other fields. It is used most in the social and behavioral sciences. A definition of SEM is difficult without reference to highly technical language, but a good starting place is the name itself.

**Quantitative psychology** is a field of scientific study that focuses on the mathematical modeling, research design and methodology, and statistical analysis of psychological processes. It includes tests and other devices for measuring cognitive abilities. Quantitative psychologists develop and analyze a wide variety of research methods, including those of psychometrics, a field concerned with the theory and technique of psychological measurement.

In statistics, a **confounder** is a variable that influences both the dependent variable and independent variable, causing a spurious association. Confounding is a causal concept, and as such, cannot be described in terms of correlations or associations. The existence of confounders is an important quantitative explanation why correlation does not imply causation.

* Designing Social Inquiry: Scientific Inference in Qualitative Research* is an influential 1994 book written by Gary King, Robert Keohane, and Sidney Verba that lays out guidelines for conducting qualitative research. The central thesis of the book is that qualitative and quantitative research share the same "logic of inference." The book primarily applies lessons from regression-oriented analysis to qualitative research, arguing that the same logics of causal inference can be used in both types of research.

Statistics, in the modern sense of the word, began evolving in the 18th century in response to the novel needs of industrializing sovereign states. The evolution of statistics was, in particular, intimately connected with the development of European states following the peace of Westphalia (1648), and with the development of probability theory, which put statistics on a firm theoretical basis.

**Quantitative methods** provide the primary research methods for studying the distribution and causes of *crime*. Quantitative methods provide numerous ways to obtain data that are useful to many aspects of society. The use of quantitative methods such as survey research, field research, and evaluation research as well as others. The data can, and is often, used by criminologists and other social scientists in making causal statements about variables being researched.

**David Collier** is an American political scientist specializing in comparative politics. He is Chancellor's Professor Emeritus at the University of California, Berkeley. He works in the fields of comparative politics, Latin American politics, and methodology. His father was the anthropologist Donald Collier.

**Andrew Gelman** is an American statistician, professor of statistics and political science at Columbia University. He earned a bachelor's degree in mathematics and in physics from MIT, where he was a National Merit Scholar, in 1986. He then earned a Ph.D. in statistics from Harvard University in 1990 under the supervision of Donald Rubin.

**Causal analysis** is the field of experimental design and statistics pertaining to establishing cause and effect. Typically it involves establishing four elements: correlation, sequence in time, a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the possibility of common and alternative ("special") causes. Such analysis usually involves one or more artificial or natural experiments.

**Causal inference** is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. The science of why things occur is called etiology. Causal inference is said to provide the evidence of causality theorized by causal reasoning.

In statistics, econometrics, epidemiology, genetics and related disciplines, **causal graphs** are probabilistic graphical models used to encode assumptions about the data-generating process.

Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. **Exploratory causal analysis** (**ECA**), also known as **data causality** or **causal discovery** is the use of statistical algorithms to infer associations in observed data sets that are potentially causal under strict assumptions. ECA is a type of causal inference distinct from causal modeling and treatment effects in randomized controlled trials. It is exploratory research usually preceding more formal causal research in the same way exploratory data analysis often precedes statistical hypothesis testing in data analysis

- ↑ A. Quetelet, Physique Sociale, https://archive.org/details/physiquesociale00quetgoog
- ↑ Edgeworth, F. Y. (1885). "On Methods of Ascertaining Variations in the Rate of Births, Deaths, and Marriages".
*Journal of the Statistical Society of London*.**48**(4): 628–649. doi:10.2307/2979201. JSTOR 2979201. - ↑ Yule, G. U. (1895). "On the Correlation of total Pauperism with Proportion of Out-Relief".
*The Economic Journal*.**5**(20): 603–611. doi:10.2307/2956650. JSTOR 2956650. - ↑ K. Pearson, The Chances of Death, and Other Studies in Evolution, 1897 https://archive.org/details/chancesdeathand00peargoog
- ↑ V. Pareto, Cours d'Économie Politique, vol. II, 1897
- ↑ Guttman, L. (1944). "A Basis for Scaling Qualitative Data".
*The American Sociological Review*.**9**(20): 603–611. JSTOR 2086306. - ↑ A. Bowley, Wages and income in the United kingdom since 1860, 1937
- ↑ W. Phillips, The Relation Between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957, published 1958
- 1 2 Miller, Delbert C., & Salkind, Neil J (2002),
*Handbook of Research Design and Social Measurement*, California: Sage, ISBN 0-7619-2046-3`{{citation}}`

: CS1 maint: multiple names: authors list (link) - 1 2 3 Hoffman, Frederick (1908). "Problems of Social Statistics and Social Research".
*Publications of the American Statistical Association*.**11**(82). - ↑ Willcox, Walter (1908). "The Need of Social Statistics as an Aid to the Courts".
*Publications of the American Statistical Association*.**13**(82). - ↑ Mitchell, Wesley (1919). "Statistics and Government".
*Publications of the American Statistical Association*.**16**(125). - ↑ 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.
- ↑ J. Pearl, Bayesianism and causality, or, why I am only a half-bayesian http://ftp.cs.ucla.edu/pub/stat_ser/r284-reprint.pdf

This article's use of external links may not follow Wikipedia's policies or guidelines.(November 2015) |

- Statistics at Curlie

- Social science statistics centers

- Center for Statistics and Social Sciences, University of Washington
- Center for the Promotion of Research Involving Innovative Statistical Methodology, New York University, NY
- Centre for Research Methods, Faculty of Social Sciences, University of Helsinki, Finland
- Cornell Institute for Social and Economic Research
- Harvard Institute for Quantitative Social Science
- Inter-University Consortium for Political and Social Research
- National Centre for Research Methods, UK
- Odum Institute for Research in Social Sciences, University of North Carolina, Chapel Hill
- Social Science Statistics Center, University of Missouri, Columbia
- Social Statistics Department, University of Manchester
- Social Statistics Division, School of Social Sciences, University of Southampton, UK
- links section)
- Social Statistics Research Group, University of Auckland, New Zealand

- Statistical databases for social science

- Inter-University Consortium for Political and Social Research
- UN Statistics Division- Demographic and Social Statistics
- Organisation for Economic Co-Operation and Development (OECD)
- US Bureau of Labor Statistics
- International Labour Organisation- LABORSTA
- Labor Research Association- Statistics for Labor Economics
- Labor and Worklife Program- Labor Stats at Harvard Law School
- Unionstats.com
- Social Statistics 2.0

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