Bowers D. Medical Statistics from Scratch: An Introduction for Health Professionals

3-rd edition. Wiley. 2014. — 408 p.
This long awaited second edition of this bestseller continues to provide a comprehensive, user friendly, down-to-earth guide to elementary statistics. The book presents a detailed account of the most important procedures for the analysis of data, from the calculation of simple proportions, to a variety of statistical tests, and the use of regression models for modeling of clinical outcomes.
The level of mathematics is kept to a minimum to make the material easily accessible to the novice, and a multitude of illustrative cases are included in every chapter, drawn from the current research literature. The new edition has been completely revised and updated and includes new chapters on basic quantitative methods, measuring survival, measurement scales, diagnostic testing, bayesian methods, meta-analysis and systematic reviews.Some fundamental stuff.
First things first – the nature of data.
Descriptive statistics.
Describing data with tables.
Describing data with charts.
Describing data from its distributional shape Learning objectives.
Describing data with numeric summary values.
Getting the data.
Doing it right first time – designing a study Learning objectives.
From little to large – statistical inference.
From samples to populations – making inferences.
Probability, risk and odds
The informed guess - confidence interval estimation.
Estimating the value of a single population parameter - the idea of confidence intervals.
Estimating the differences between two population parameters.
Estimating the ratio of two population parameters.
Putting it to the test.
Testing hypotheses about the difference between two population parameters.
Testing hypotheses about the ratio of two population parameters.
Testing hypotheses about the equality of two or more proportions.
Getting up close.
Measuring the association between two variables.
Measuring the agreement between two variables.
Getting into a relationship.
Straight-line models - linear regression.
Curvy models - logistic regression.
Two more chapters.
Measuring survival.
Systematic review and meta-analysis.
Appendix: Table of random numbers.
Solutions to Exercises.