000 03993nam a22004935i 4500
001 978-3-642-16313-5
003 DE-He213
005 20140220083748.0
007 cr nn 008mamaa
008 101112s2011 gw | s |||| 0|eng d
020 _a9783642163135
_9978-3-642-16313-5
024 7 _a10.1007/978-3-642-16313-5
_2doi
050 4 _aT57-57.97
072 7 _aPBW
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aVasishth, Shravan.
_eauthor.
245 1 4 _aThe Foundations of Statistics: A Simulation-based Approach
_h[electronic resource] /
_cby Shravan Vasishth, Michael Broe.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2011.
300 _aXVI, 178p. 25 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1. Getting Started -- 2. Randomness and Probability -- 3. The Sampling Distribution of the Sample Mean -- 4. Power -- 5. Analysis of Variance (NOVA) -- 6. Bivariate Statistics and Linear Models -- 7. An Introduction to Linear Mixed Models. A. Random Variables -- B- Basic R Commands and Data Structures -- Index -- References.
520 _aStatistics and hypothesis testing are routinely used in areas (such as linguistics) that are traditionally not mathematically intensive. In such fields, when faced with experimental data, many students and researchers tend to rely on commercial packages to carry out statistical data analysis, often without understanding the logic of the statistical tests they rely on. As a consequence, results are often misinterpreted, and users have difficulty in flexibly applying techniques relevant to their own research — they use whatever they happen to have learned. A simple solution is to teach the fundamental ideas of statistical hypothesis testing without using too much mathematics. This book provides a non-mathematical, simulation-based introduction to basic statistical concepts and encourages readers to try out the simulations themselves using the source code and data provided (the freely available programming language R is used throughout). Since the code presented in the text almost always requires the use of previously introduced programming constructs, diligent students also acquire basic programming abilities in R. The book is intended for advanced undergraduate and graduate students in any discipline, although the focus is on linguistics, psychology, and cognitive science. It is designed for self-instruction, but it can also be used as a textbook for a first course on statistics. Earlier versions of the book have been used in undergraduate and graduate courses in Europe and the US.   ”Vasishth and Broe have written an attractive introduction to the foundations of statistics. It is concise, surprisingly comprehensive, self-contained and yet quite accessible. Highly recommended.” Harald Baayen, Professor of Linguistics, University of Alberta, Canada   ”By using the text students not only learn to do the specific things outlined in the book, they also gain a skill set that empowers them to explore new areas that lie beyond the book’s coverage.” Colin Phillips, Professor of Linguistics, University of Maryland, USA
650 0 _aMathematics.
650 0 _aData mining.
650 0 _aPsycholinguistics.
650 0 _aPhilosophy (General).
650 1 4 _aMathematics.
650 2 4 _aApplications of Mathematics.
650 2 4 _aPsycholinguistics.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aMathematics Education.
650 2 4 _aPsychology, general.
700 1 _aBroe, Michael.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642163128
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-16313-5
912 _aZDB-2-SMA
999 _c107145
_d107145