000 03419nam a22004215i 4500
001 978-4-431-54321-3
003 DE-He213
005 20140220082524.0
007 cr nn 008mamaa
008 131008s2014 ja | s |||| 0|eng d
020 _a9784431543213
_9978-4-431-54321-3
024 7 _a10.1007/978-4-431-54321-3
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aTakezawa, Kunio.
_eauthor.
245 1 0 _aLearning Regression Analysis by Simulation
_h[electronic resource] /
_cby Kunio Takezawa.
264 1 _aTokyo :
_bSpringer Japan :
_bImprint: Springer,
_c2014.
300 _aXII, 300 p. 88 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
520 _aThe standard approach of most introductory books for practical statistics is that readers first learn the minimum mathematical basics of statistics and rudimentary concepts of statistical methodology. They then are given examples of analyses of data obtained from natural and social phenomena so that they can grasp practical definitions of statistical methods. Finally they go on to acquaint themselves with statistical software for the PC and analyze similar data to expand and deepen their understanding of statistical methods. This book, however, takes a slightly different approach, using simulation data instead of actual data to illustrate the functions of statistical methods. Also, "R" programs listed in the book help readers realize clearly how these methods work to bring intrinsic values of data to the surface. "R" is free software enabling users to handle vectors, matrices, data frames, and so on. For example, when a statistical theory indicates that an event happens with a 5 % probability, readers can confirm the fact using "R" programs that this event actually occurs with roughly that probability, by handling data generated by pseudo-random numbers. Simulation gives readers populations with known backgrounds and the nature of the population can be adjusted easily. This feature of the simulation data helps provide a clear picture of statistical methods painlessly. Most readers of introductory books of statistics for practical purposes do not like complex mathematical formulae, but they do not mind using a PC to produce various numbers and graphs by handling a huge variety of numbers. If they know the characteristics of these numbers beforehand, they treat them with ease. Struggling with actual data should come later. Conventional books on this topic frighten readers by presenting unidentified data to them indiscriminately. This book provides a new path to statistical concepts and practical skills in a readily accessible manner.
650 0 _aStatistics.
650 0 _aMathematical statistics.
650 1 4 _aStatistics.
650 2 4 _aStatistical Theory and Methods.
650 2 4 _aStatistics and Computing/Statistics Programs.
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9784431543206
856 4 0 _uhttp://dx.doi.org/10.1007/978-4-431-54321-3
912 _aZDB-2-SMA
999 _c93680
_d93680