000			03494cam a2200385 a 4500
001			15338358
003			EG-ScBUE
005			20220407095854.0
008			080620r20142008enka f b 001 0 eng d
020			_a0521709180 (pbk.)
020			_a9780521709187 (pbk.)
035			_a(OCoLC)ocn166626226
040			_aUKM _beng _erda _cUKM _dEG-ScBUE _dEG-ScBUE
082	0	4	_a410.151 _bBAA _222
100	1		_aBaayen, R. Harald‏, _eauthor. _941186
245	1	0	_aAnalyzing linguistic data : _ba practical introduction to statistics using R / _cR. H. Baayen.
250			_aSeventh printing.
264		1	_aCambridge : _bCambridge University Press, _c2014.
300			_axiii, 353 pages : _billustrations ; _c26 cm
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
504			_aIncludes bibliographical references and index.
505			_a1. An introduction to R: 1.1. R as a calculator -- 1.2. Getting data into and out of R -- 1.3. Accessing information in data frames -- 1.4. Operations on data frames -- 1.5. Session management -- 2. Graphical data exploration: 2.1. Random variables -- 2.2. Visualizing single random variables -- 2.3. Visualizing two or more variables -- 2.4. Trellis graphics -- 3. Probability distributions: 3.1. Distributions -- 3.2. Discrete distributions -- 3.3. Continuous distributions -- 4. Basic statistical methods: 4.1. Tests for single vectors -- 4.2. Tests for two independent vectors -- 4.3. Paired vectors -- 4.4. A numerical vector and a factor: analysis of variance -- 4.5. Two vectors with counts -- 4.6. A note on statistical significance -- 5. Clustering and classification: 5.1. Clustering -- 5.2. Classification -- 6. Regression modeling: 6.1. Introduction -- 6.2. Ordinary least squares regression -- 6.3. Generalized linear models -- 6.4. Regression with breakpoints -- 6.5. Models for lexical richness -- 6.6. General considerations -- 7. Mixed models: 7.1. Modeling data with fixed and random effects -- 7.2. comparison with traditional analyses -- 7.3. Shrinkage in mixed-effects models -- 7.4. Generalized linear mixed models -- 7.5. Case studies.
520			_a"This textbook provides a straightforward introduction to the statistical analysis of language data. It clearly introduces the basic principles and methods of statistical analysis, using R, the leading computational statistics programming environment. The reader is guided step-by-step through a range of real data sets, allowing them to analyze phonetic data, construct phylogenetic trees, quantify register variation in corpus linguistics, and analyze experimental data using state-of-the-art models. The visualization of data plays a key role, both in the early stages of data exploration and later on when the reader is encouraged to criticize initial models fitted to the data. Containing over forty exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data."
650		7	_aMathematical linguistics. _2BUEsh _941185
650		7	_aLinguistics _xStatistical methods. _2BUEsh _941184
650		7	_aComputational linguistics. _2BUEsh _94459
650		7	_aR (Computer program language). _920132 _2BUEsh
651			_2BUEsh
653			_bHHUUEENN _cSeptember2016 _cOctober2018
655			_vReading book _934232
856	4	1	_3Table of contents only _uhttp://www.loc.gov/catdir/toc/fy0805/2008299641.html
942			_2ddc _cBB
999			_c22388 _d22360