(Ebook) Statistical Methods for the Analysis of Biomedical Data, Second Edition by Robert F. Woolson, William R. Clarke(auth.) ISBN 9780471394051, 9781118033050, 047139405X, 1118033051

(Ebook) Statistical Methods for the Analysis of Biomedical Data, Second Edition by Robert F. Woolson, William R. Clarke(auth.) ISBN 9780471394051, 9781118033050, 047139405X, 1118033051

The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.
* Organized by problem rather than method, so it guides readers to the correct technique for solving the problem at hand.Content:
Chapter 1 Introduction (pages 1–8):
Chapter 2 Descriptive Statistics (pages 9–48):
Chapter 3 Basic Probability Concepts (pages 49–77):
Chapter 4 Further Aspects of Probability (pages 79–118):
Chapter 5 Confidence Intervals and Hypothesis Testing: General Considerations and Applications (pages 119–149):
Chapter 6 Comparison of Two Groups: t?Tests and Rank Tests (pages 151–216):
Chapter 7 Comparison of Two Groups: Chi?Square and Related Procedures (pages 217–262):
Chapter 8 Tests of Independence and Measures of Association for Two Random Variables (pages 263–306):
Chapter 9 Least?Squares Regression Methods: Predicting One Variable from Another (pages 307–357):
Chapter 10 Comparing More than Two Groups of Observations: Analysis of Variance for Comparing Groups (pages 359–415):
Chapter 11 Comparing More than Two Groups of Observations: Rank Analysis of Variance for Group Comparisons (pages 417–439):
Chapter 12 Comparing More than Two Groups of Observations: Chi?Square and Related Procedures (pages 441–460):
Chapter 13 Special Topics in Analysis of Epidemiologic and Clinical Data: Studying Association between a Disease and a Characteristic (pages 461–507):
Chapter 14 Estimation and Comparison of Survival Curves (pages 509–540):
Chapter 15 Multiple Linear Regression Methods: Predicting One Variable from Two or More Other Variables (pages 541–622):