Intuitive biostatistics : a nonmathematical guide to statistical thinking
 Author/Creator
 Motulsky, Harvey.
 Language
 English.
 Imprint
 Completely rev. 2nd ed.  New York : Oxford University Press, 2010.
 Physical description
 1 v. (various pagings) : ill. ; 24 cm.
Access
Available online

Stacks

Unknown
R853 .S7 M68 2010

Unknown
R853 .S7 M68 2010
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Contents/Summary
 Bibliography
 Includes bibliographical references and index.
 Contents

 Statistics 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 : casecontrolled studies
 Comparing survival curves
 Comparing two means : unpaired ttest
 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 receiveroperator characteristic curves
 Sample size
 Statistical advice
 Choosing a statistical test
 Capstone example
 Review problems
 Answers to review problems.
 Summary
 "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 multipart problems, with answers fully discussed in Chapter 48. New "Q and A" sections throughout the book review key concepts"Provided by publisher.
Subjects
Bibliographic information
 Publication date
 2010
 Responsibility
 Harvey Motulsky.
 ISBN
 9780199730063
 0199730067