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Variation Analysis
Variable rules analysis is a set of statistical analysis methods in linguistics that are commonly used in sociolinguistics and historical linguistics to describe patterns of variation between alternative forms in language use. It is also sometimes known as Varbrul analysis, after the name of a software package dedicated to carrying out the relevant statistical computations (''Varbrul'', from "variable rule"). The method goes back to a theoretical approach developed by the sociolinguist William Labov in the late 1960s and early 1970s, and its mathematical implementation was developed by Henrietta Cedergren and David Sankoff in 1974. A variable rules analysis is designed to provide a quantitative model of a situation where speakers alternate between different forms that have the same meaning and stand in free variation, but in such a way that the probability of choice of either the one or the other form is conditioned by a variety of context factors or social characteristics. Such a ...
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Statistical Analysis
Statistical inference is the process of using data analysis to infer properties of an underlying probability distribution.Upton, G., Cook, I. (2008) ''Oxford Dictionary of Statistics'', OUP. . Inferential statistical analysis infers properties of a Statistical population, population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is Sampling (statistics), sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population. In machine learning, the term ''inference'' is sometimes used instead to mean "make a prediction, by evaluating an already trained model"; in this context inferring properties of the model is referred to as ''training'' or ''learning'' (rather than ''inference''), and using a model for prediction is referred to as ...
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Maximum Likelihood
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable. The point in the parameter space that maximizes the likelihood function is called the maximum likelihood estimate. The logic of maximum likelihood is both intuitive and flexible, and as such the method has become a dominant means of statistical inference. If the likelihood function is differentiable, the derivative test for finding maxima can be applied. In some cases, the first-order conditions of the likelihood function can be solved analytically; for instance, the ordinary least squares estimator for a linear regression model maximizes the likelihood when the random errors are assumed to have normal distributions with the same variance. From the perspective of Bayesian inference, ML ...
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Linguistic Research Software
Linguistics is the scientific study of language. The areas of linguistic analysis are syntax (rules governing the structure of sentences), semantics (meaning), morphology (structure of words), phonetics (speech sounds and equivalent gestures in sign languages), phonology (the abstract sound system of a particular language, and analogous systems of sign languages), and pragmatics (how the context of use contributes to meaning). Subdisciplines such as biolinguistics (the study of the biological variables and evolution of language) and psycholinguistics (the study of psychological factors in human language) bridge many of these divisions. Linguistics encompasses many branches and subfields that span both theoretical and practical applications. Theoretical linguistics is concerned with understanding the universal and fundamental nature of language and developing a general theoretical framework for describing it. Applied linguistics seeks to utilize the scientific findings of the ...
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Diaphoneme
A diaphoneme is an abstract phonology, phonological unit that identifies a correspondence between related sounds of two or more variety (linguistics), varieties of a language or language cluster. For example, some English varieties contrast the vowel of ''late'' () with that of ''wait'' or ''eight'' (). Other English varieties contrast the vowel of ''late'' or ''wait'' () with that of ''eight'' (). This non-overlapping pair of phonemes from two different varieties can be reconciled by positing three different diaphonemes: A first diaphoneme for words like ''late'' (), a second diaphoneme for words like ''wait'' (), and a third diaphoneme for words like ''eight'' (). Diaphonology studies the realization of diaphones across dialects, and is important if an orthography is to be adequate for more than one dialect of a language. In historical linguistics, it is concerned with the reflexes of an ancestral phoneme as a language splits into dialects, such as the modern realizations of O ...
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R (programming Language)
R is a programming language for statistical computing and Data and information visualization, data visualization. It has been widely adopted in the fields of data mining, bioinformatics, data analysis, and data science. The core R language is extended by a large number of R package, software packages, which contain Reusability, reusable code, documentation, and sample data. Some of the most popular R packages are in the tidyverse collection, which enhances functionality for visualizing, transforming, and modelling data, as well as improves the ease of programming (according to the authors and users). R is free and open-source software distributed under the GNU General Public License. The language is implemented primarily in C (programming language), C, Fortran, and Self-hosting (compilers), R itself. Preprocessor, Precompiled executables are available for the major operating systems (including Linux, MacOS, and Microsoft Windows). Its core is an interpreted language with a na ...
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Microsoft Windows
Windows is a Product lining, product line of Proprietary software, proprietary graphical user interface, graphical operating systems developed and marketed by Microsoft. It is grouped into families and subfamilies that cater to particular sectors of the computing industry – Windows (unqualified) for a consumer or corporate workstation, Windows Server for a Server (computing), server and Windows IoT for an embedded system. Windows is sold as either a consumer retail product or licensed to Original equipment manufacturer, third-party hardware manufacturers who sell products Software bundles, bundled with Windows. The first version of Windows, Windows 1.0, was released on November 20, 1985, as a graphical operating system shell for MS-DOS in response to the growing interest in graphical user interfaces (GUIs). The name "Windows" is a reference to the windowing system in GUIs. The 1990 release of Windows 3.0 catapulted its market success and led to various other product families ...
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Mac OS
Mac operating systems were developed by Apple Inc. in a succession of two major series. In 1984, Apple debuted the operating system that is now known as the classic Mac OS with its release of the original Macintosh System Software. The system, rebranded Mac OS in 1997, was pre-installed on every Macintosh until 2002 and offered on Macintosh clones shortly in the 1990s. It was noted for its ease of use, and also criticized for its lack of modern technologies compared to its competitors. The current Mac operating system is macOS, originally named Mac OS X until 2012 and then OS X until 2016. It was developed between 1997 and 2001 after Apple's purchase of NeXT. It brought an entirely new architecture based on NeXTSTEP, a Unix system, that eliminated many of the technical challenges that the classic Mac OS faced, such as problems with memory management. The current macOS is pre-installed with every Mac and receives a major update annually. It is the basis of Apple's current syst ...
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Freeware
Freeware is software, often proprietary, that is distributed at no monetary cost to the end user. There is no agreed-upon set of rights, license, or EULA that defines ''freeware'' unambiguously; every publisher defines its own rules for the freeware it offers. For instance, modification, redistribution by third parties, and reverse engineering are permitted by some publishers but prohibited by others. Unlike with free and open-source software, which are also often distributed free of charge, the source code for freeware is typically not made available. Freeware may be intended to benefit its producer by, for example, encouraging sales of a more capable version, as in the freemium and shareware business models. History The term ''freeware'' was coined in 1982 by Andrew Fluegelman, who wanted to sell PC-Talk, the communications application he had created, outside of commercial distribution channels. Fluegelman distributed the program via the same process as ''shareware''. As s ...
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SPSS
SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc., it was acquired by IBM in 2009. Versions of the software released since 2015 have the brand name IBM SPSS Statistics. The software name originally stood for Statistical Package for the Social Sciences (SPSS), reflecting the original market, then later changed to Statistical Product and Service Solutions. Overview SPSS is a widely used program for statistics, statistical analysis in social science. It is also used by market researchers, health researchers, survey companies, government, education researchers, industries, marketing organizations, data miners, and others. The original SPSS manual (Nie, Bent & Hull, 1970) has been described as one of "sociology's most influential books" for allowing ordinary researchers to do their own statistical analysis. In addition to statist ...
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Logistic Regression
In statistics, a logistic model (or logit model) is a statistical model that models the logit, log-odds of an event as a linear function (calculus), linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) estimation theory, estimates the parameters of a logistic model (the coefficients in the linear or non linear combinations). In binary logistic regression there is a single binary variable, binary dependent variable, coded by an indicator variable, where the two values are labeled "0" and "1", while the independent variables can each be a binary variable (two classes, coded by an indicator variable) or a continuous variable (any real value). The corresponding probability of the value labeled "1" can vary between 0 (certainly the value "0") and 1 (certainly the value "1"), hence the labeling; the function that converts log-odds to probability is the logistic function, hence the name. The unit of measurement for the ...
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Sociolinguistics
Sociolinguistics is the descriptive, scientific study of how language is shaped by, and used differently within, any given society. The field largely looks at how a language changes between distinct social groups, as well as how it varies under the influence of assorted cultural norms, expectations, and contexts. Sociolinguistics combines the older field of dialectology with the social sciences in order to identify regional dialects, sociolects, ethnolects, and other sub-varieties and styles within a language, as well as the distinctions and variations inside each of these. A major branch of linguistics since the second half of the 20th century, sociolinguistics is closely related to and can partly overlap with pragmatics, linguistic anthropology, and sociology of language, the latter focusing on the effect of language back on society. Sociolinguistics' historical interrelation with anthropology can be observed in studies of how language varieties differ between groups ...
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Stepwise Regression
In statistics, stepwise regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure. In each step, a variable is considered for addition to or subtraction from the set of explanatory variables based on some prespecified criterion. Usually, this takes the form of a forward, backward, or combined sequence of ''F''-tests or ''t''-tests. The frequent practice of fitting the final selected model followed by reporting estimates and confidence intervals without adjusting them to take the model building process into account has led to calls to stop using stepwise model building altogetherFlom, P. L. and Cassell, D. L. (2007) "Stopping stepwise: Why stepwise and similar selection methods are bad, and what you should use," NESUG 2007. or to at least make sure model uncertainty is correctly reflected by using prespecified, automatic criteria together with more complex standard error estimates that remain unbiased. ...
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