000 03041nam a22004455i 4500
001 978-1-4614-0394-4
003 DE-He213
005 20140220083732.0
007 cr nn 008mamaa
008 110712s2011 xxu| s |||| 0|eng d
020 _a9781461403944
_9978-1-4614-0394-4
024 7 _a10.1007/978-1-4614-0394-4
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aPD
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aVidakovic, Brani.
_eauthor.
245 1 0 _aStatistics for Bioengineering Sciences
_h[electronic resource] :
_bWith MATLAB and WinBUGS Support /
_cby Brani Vidakovic.
250 _a1.
264 1 _aNew York, NY :
_bSpringer New York,
_c2011.
300 _aXVI, 753p. 190 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Texts in Statistics,
_x1431-875X
505 0 _aIntroduction -- The Sample and Its Properties -- Probability, Conditional Probability, and Bayes' Rule -- Sensitivity, Specificity, and Relatives -- Random Variables -- Normal Distribution -- Point and Interval Estimators -- Bayesian Approach to Inference -- Testing Statistical Hypotheses -- Two Samples -- ANOVA and Elements of Experimental Design -- Distribution-Free Tests -- Goodness-of-Fit Tests -- Models for Tables -- Correlation -- Regression -- Regression for Binary and Count Data -- Inference for Censored Data and Survival Analysis -- Bayesian Inference Using Gibbs Sampling - BUGS Project.
520 _aThrough its scope and depth of coverage, this book addresses the needs of the vibrant and rapidly growing engineering fields, bioengineering and biomedical engineering, while implementing software that engineers are familiar with. The author integrates introductory statistics for engineers and  introductory biostatistics as a single textbook heavily oriented to computation and hands on approaches. For example, topics ranging from the aspects of disease and device testing, Sensitivity, Specificity and ROC curves, Epidemiological Risk Theory, Survival Analysis, or Logistic and Poisson Regressions are covered. In addition to the synergy of engineering and biostatistical approaches, the novelty of this book is in the substantial coverage of Bayesian approaches to statistical inference. Many examples in this text are solved using both the traditional and Bayesian methods, and the results are compared and commented.
650 0 _aStatistics.
650 1 4 _aStatistics.
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:
_z9781461403937
830 0 _aSpringer Texts in Statistics,
_x1431-875X
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-0394-4
912 _aZDB-2-SMA
999 _c106247
_d106247