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The present book finds and collects absolutely new aspects of word frequency. First, eminent characteristics (such as the h-point, first used in scientometrics, the k-, m-, and n-points) are introduced - it can be shown that the geometry of word frequency is fundamentally based on them. Furthermore, various indicators of text properties are proposed for the first time, such as thematic concentration, autosemantic text compactness, autosemantic density, etc. In detail, the autosemantic structure of a given text is evaluated by means of a graph representation and its properties (according to a problem from network research). Special emphasis is given to the part-of-speech differentiation, which plays a significant role in stylistics. On the basis of a general theory, which has been developed especially for linguistic research, problems of the frequency structure of texts with respect to word occurrence are investigated and discussed in detail. Methodologically, specific reference is made to synergetic linguistics, including some exemplary analyses, showing that there are points of contact with this field. A separate chapter is dedicated to within-sentence word position; this issue considers grammar as well as language genesis; another chapter is dedicated to the type-token ratio, discussing all established methods and their relevance for word frequency analysis. All methods presented in the book are statistically tested; to this end, some new tests have been developed. All procedures and calculations are conducted for 20 languages, ranging from Polynesia, Indonesia, India, and Europe to a North American Indian language. The broad distribution of the data and texts from all genres allows generalizations with respect to language typology.
Language and languages --- Linguistics. --- Linguistic science --- Science of language --- Frequency counts of words --- Frequency word lists --- Word counts --- Word frequency --- Frequency (Linguistics) --- Linguistics --- Vocabulary --- Word frequency. --- Statistical methods --- Mathematical linguistics --- Linguistic Data. --- Statistic Analysis. --- Text Structure. --- Typology.
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This book is an introduction to statistics for linguists using the open source software R. It is aimed at students and instructors/professors with little or no statistical background and is written in a non-technical and reader-friendly/accessible style. It first introduces in detail the overall logic underlying quantitative studies: exploration, hypothesis formulation and operationalization, and the notion and meaning of significance tests. It then introduces some basics of the software R relevant to statistical data analysis. A chapter on descriptive statistics explains how summary statistics for frequencies, averages, and correlations are generated with R and how they are graphically represented best. A chapter on analytical statistics explains how statistical tests are performed in R on the basis of many different linguistic case studies: For nearly every single example, it is explained what the structure of the test looks like, how hypotheses are formulated, explored, and tested for statistical significance, how the results are graphically represented, and how one would summarize them in a paper/article. A chapter on selected multifactorial methods introduces how more complex research designs can be studied: methods for the study of multifactorial frequency data, correlations, tests for means, and binary response data are discussed and exemplified step-by-step. Also, the exploratory approach of hierarchical cluster analysis is illustrated in detail. The book comes with many exercises, boxes with short think breaks and warnings, recommendations for further study, and answer keys as well as a statistics for linguists newsgroup on the companion website. The volume is aimed at beginners on every level of linguistic education: undergraduate students, graduate students, and instructors/professors and can be used in any research methods and statistics class for linguists. It presupposes no quantitative/statistical knowledge whatsoever and, unlike most competing books, begins at step 1 for every method and explains everything explicitly.
Programming --- Mathematical linguistics --- Mathematical statistics --- Linguistics --- R (Computer program language) --- Linguistique --- R (Langage de programmation) --- Statistical methods --- Méthodes statistiques --- Computational linguistics. --- Computational logistics. --- Linguistics -- Statistical methods. --- R (Computer program language). --- Languages & Literatures --- Philology & Linguistics --- #KVHA:Methodologie --- #KVHA:Statistiek --- #KVHA:Taalkunde --- Computerlinguïstiek --- Linguïstiek --- R (programmeertaal) --- Statistical methods. --- statistische methoden --- Computerlinguïstiek. --- R (programmeertaal). --- statistische methoden. --- Méthodes statistiques --- GNU-S (Computer program language) --- Language and languages --- Linguistics, Statistical --- Statistical linguistics --- Domain-specific programming languages --- Linguistics - Statistical methods --- Corpus Linguistics. --- Linguistic Data. --- Statistic Analysis.
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