000			04224nam a2200505 i 4500
001			6813238
003			IEEE
005			20200413152851.0
006			m eo d
007			cr cn |||m|||a
008			081015s2008 caua foab 000 0 eng d
020			_a9781598297782 (electronic bk.)
020			_a9781598297775 (pbk.)
024	7		_a10.2200/S00142ED1V01Y200807MAS001 _2doi
035			_a(OCoLC)241487825
035			_a(CaBNVSL)gtp00531468
040			_aCaBNVSL _cCaBNVSL _dCaBNVSL
050		4	_aQA278.8 _b.S527 2008
082	0	4	_a519.5 _222
100	1		_aShasha, Dennis Elliott.
245	1	0	_aStatistics is easy! _h[electronic resource] / _cDennis Shasha, Manda Wilson.
260			_aSan Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : _bMorgan & Claypool Publishers, _cc2008.
300			_a1 electronic text (vi, 70 p. : ill.) : _bdigital file.
490	1		_aSynthesis lectures on mathematics and statistics ; _v#1
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat Reader.
500			_aPart of: Synthesis digital library of engineering and computer science.
500			_aSeries from website.
504			_aIncludes bibliographical references (p. 69-70).
505	0		_aThe basic idea -- Bias corrected confidence intervals -- Pragmatic considerations when using resampling -- Terminology -- The essential stats -- Mean -- Why and when -- Calculate -- Example -- Pseudocode & code -- Difference between two means -- Why and when -- Calculate -- Example -- Pseudocode & code -- Chi-squared -- Why and when -- Calculate with example -- Pseudocode & code -- Calculate with example for multiple variables -- Pseudocode & code -- Fisher S exact test -- Why and when -- Calculate with example -- Pseudocode & code -- One-way ANOVA -- Why and when -- Calculate with example -- Statistics is easy -- Pseudocode & code -- Multi-way ANOVA -- Why and when -- Calculate with example -- Pseudocode & code -- Linear regression -- Why and when -- Calculate with example -- Pseudocode & code -- Linear correlation -- Why and when -- Calculate & example -- Pseudocode & code -- Multiple regression -- Multiple testing -- Why and when -- Family wise error rate -- False discovery rate -- Case study: New Mexico's 2004 presidential ballots -- Take a close look at the data -- What questions do we want to ask -- How do we attempt to answer this question -- Next: effect of ethnicity for each machine type -- We have used the following techniques -- What did we find out?
506	1		_aAbstract freely available; full-text restricted to subscribers or individual document purchasers.
510	0		_aCompendex
510	0		_aINSPEC
510	0		_aGoogle scholar
510	0		_aGoogle book search
520			_aStatistics is the activity of inferring results about a population given a sample. Historically, statistics books assume an underlying distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot normally be sure of the underlying distribution. For that reason, this book presents a distribution-independent approach to statistics based on a simple computational counting idea called resampling. This book explains the basic concepts of resampling, then systematically presents the standard statistical measures along with programs (in the language Python) to calculate them using resampling, and finally illustrates the use of the measures and programs in a case study. The text uses junior high school algebra and many examples to explain the concepts. The ideal reader has mastered at least elementary mathematics, likes to think procedurally, and is comfortable with computers.
530			_aAlso available in print.
588			_aTitle from PDF t.p. (viewed on October 15, 2008).
650		0	_aNonparametric statistics.
650		0	_aResampling (Statistics)
700	1		_aWilson, Manda.
730	0		_aSynthesis digital library of engineering and computer science.
830		0	_aSynthesis lectures on mathematics and statistics ; _v#1.
856	4	2	_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6813238
999			_c561619 _d561619