MARC Record from Library of Congress

LEADER: 04295cam a22003494a 4500
001 2009046932
003 DLC
005 20100710085622.0
008 091119s2010 nyua b 001 0 eng
010 $a 2009046932
016 7 $a101519790$2DNLM
020 $a9780199730063 (pbk. : alk. paper)
020 $a0199730067 (pbk. : alk. paper)
035 $a(OCoLC)ocn470694492
040 $aDNLM/DLC$cDLC$dBTCTA$dNLM$dYDXCP$dC#P$dBWX$dCDX$dAGL$dDLC
042 $apcc
050 00 $aR853.S7$bM68 2010
060 00 $a2010 B-997
060 10 $aWA 950$bM922i 2010
070 0 $aR853.S7$bM68 2010
082 00 $a610.72/1$222
100 1 $aMotulsky, Harvey.
245 10 $aIntuitive biostatistics :$ba nonmathematical guide to statistical thinking /$cHarvey Motulsky.
250 $aCompletely rev. 2nd ed.
260 $aNew York :$bOxford University Press,$c2010.
300 $a1 v. (various pagings) :$bill. ;$c24 cm.
504 $aIncludes bibliographical references and index.
505 0 $aStatistics and probability are not intuitive -- Why statistics can be hard to learn -- From sample to population -- Confidence interval of a proportion -- Confidence interval of survival data -- Confidence interval of counted data -- Graphing continuous data -- Types of variables -- Quantifying scatter -- The Gaussian distribution -- The lognormal distribution and geometric mean -- Confidence interval of a mean -- The theory of confidence intervals -- Error bars -- Introducing P values -- Statistical significance and hypothesis testing -- Relationship between confidence intervals and statistical significance -- Interpreting a result that is statistically significant -- Interpreting a result that is not statistically significant -- Statistical power -- Testing for equivalence or noninferiority -- Multiple comparisons concepts -- Multiple comparisons traps -- Gaussian or not? -- Outliers -- Comparing observed and expected distributions -- Comparing proportions : prospective and experimental studies -- Comparing proportions : case-controlled studies -- Comparing survival curves -- Comparing two means : unpaired t-test -- Comparing two paired groups -- Correlation -- Simple linear regression -- Introducing models -- Comparing models -- Nonlinear regression -- Multiple, logistic, and proportional hazards regression -- Multiple regression traps -- Analysis of variance -- Multiple comparison tests after ANOVA -- Nonparametric methods -- Sensitivity, specificity, and receiver-operator characteristic curves -- Sample size -- Statistical advice -- Choosing a statistical test -- Capstone example -- Review problems -- Answers to review problems.
520 $a"Thoroughly revised and updated, the second edition of Intuitive Biostatistics retains and refines the core perspectives of the previous edition: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. Intuitive Biostatistics, Completely Revised Second Edition, provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists. New to this edition: Chapter 1 shows how our intuitions lead us to misinterpret data, thus explaining the need for statistical rigor. Chapter 11 explains the lognormal distribution, an essential topic omitted from many other statistics books. Chapter 21 contrasts testing for equivalence with testing for differences. Chapters 22, 23, and 40 explore the pervasive problem of multiple comparisons. Chapters 24 and 25 review testing for normality and outliers. Chapter 35 shows how statistical hypothesis testing can be understood as comparing the fits of alternative models. Chapters 37 and 38 provide a brief introduction to multiple, logistic, and proportional hazards regression. Chapter 46 reviews one example in great depth, reviewing numerous statistical concepts and identifying common mistakes. Chapter 47 includes 49 multi-part problems, with answers fully discussed in Chapter 48. New "Q and A" sections throughout the book review key concepts"--Provided by publisher.
650 0 $aMedicine$xResearch$xStatistical methods.
650 12 $aBiometry$xmethods.
650 22 $aBiomedical Research$xmethods.