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Social statistics is the use of statistical measurement systems to study human behavior in a social environment. Statistical finance , an area of econophysics , is an empirical attempt to shift finance from its normative roots to a positivist framework using exemplars from statistical physics with an emphasis on emergent or collective ...
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.
Typology is a composite measure that involves the classification of observations in terms of their attributes on multiple variables. [1] Such classification is usually done on a nominal scale. [1]
Simpson's paradox is a phenomenon in probability and statistics in which a trend appears in several groups of data but disappears or reverses when the groups are combined. This result is often encountered in social-science and medical-science statistics, [ 1 ] [ 2 ] [ 3 ] and is particularly problematic when frequency data are unduly given ...
Statistics is a field of inquiry that studies the collection, analysis, interpretation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities; it is also used and misused for making informed decisions in all areas of business and government.
Civic statistics is a sub-discipline of statistics focused on the analysis of evidence relevant to understanding and addressing issues of public concern such as human migration, poverty and inequality. It lies at the intersection of politics, social science, statistics, and education.
In the social sciences, scaling is the process of measuring or ordering entities with respect to quantitative attributes or traits. For example, a scaling technique might involve estimating individuals' levels of extraversion, or the perceived quality of products.
Social data scientists use both digitized data [22] (e.g. old books that have been digitized) and natively digital data (e.g. social media posts). [23] Since such data often take the form of found data that were originally produced for other purposes (commercial, governance, etc.) than research, data scraping, cleaning and other forms of preprocessing and data mining occupy a substantial part ...
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