000 02204nam a22003137a 4500
001 sulb-eb0016940
003 BD-SySUS
005 20160405140626.0
008 100601s2011||||enk o ||1 0|eng|d
020 _a9780511783708 (ebook)
020 _z9781107004306 (hardback)
020 _z9780521179232 (paperback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
_dBD-SySUS.
050 0 0 _aQH323.5
_b.E88 2011
082 0 0 _a577.0727
_222
100 1 _aEstabrook, George F.,
_eauthor.
245 1 2 _aA Computational Approach to Statistical Arguments in Ecology and Evolution /
_cGeorge F. Estabrook.
246 3 _aA Computational Approach to Statistical Arguments in Ecology & Evolution
264 1 _aCambridge :
_bCambridge University Press,
_c2011.
300 _a1 online resource (266 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _aTitle from publisher's bibliographic system (viewed on 04 Apr 2016).
520 _aScientists need statistics. Increasingly this is accomplished using computational approaches. Freeing readers from the constraints, mysterious formulas and sophisticated mathematics of classical statistics, this book is ideal for researchers who want to take control of their own statistical arguments. It demonstrates how to use spreadsheet macros to calculate the probability distribution predicted for any statistic by any hypothesis. This enables readers to use anything that can be calculated (or observed) from their data as a test statistic and hypothesize any probabilistic mechanism that can generate data sets similar in structure to the one observed. A wide range of natural examples drawn from ecology, evolution, anthropology, palaeontology and related fields give valuable insights into the application of the described techniques, while complete example macros and useful procedures demonstrate the methods in action and provide starting points for readers to use or modify in their own research.
776 0 8 _iPrint version:
_z9781107004306
856 4 0 _uhttp://dx.doi.org/10.1017/CBO9780511783708
942 _2Dewey Decimal Classification
_ceBooks
999 _c38378
_d38378