Medical statistics from scratch
著者
書誌事項
Medical statistics from scratch
J. Wiley, c2002
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注記
Includes bibliographical references (p. [198]-200) and index
内容説明・目次
内容説明
This second edition combines information from the original two books, Statistics from Scratch and Statistics Further from Scratch, to make one, 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, drown from the current research literature.
目次
Preface.Introduction.PART I: SOME FUNDAMENTAL STUFF.First Things First: the Nature of Data.PART II: DESCRIBING DATA.Describing Data with Tables.Describing Data with Charts.Describing Data from Its Distributional Shape.Describing Data with Numeric Summary Values.PART III: GETTING THE DATA.Doing It Right First Time: Designing a Study.PART IV: FROM LITTLE TO LARGE: STATISTICAL INFERENCE.From Samples to Populations: Making Inferences.Probability, Risk, and Odds.PART V: THE INFORMED GUESS: CONFIDENCE INTERVAL ESTIMATION.Estimating the Value of a Single Population Parameter.Estimating the Difference between Two Population Parameters.Estimating the Ratio of Two Population Parameters.PART VI: 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 Population Proportions.PART VII: GETTING UP CLOSE.Measuring the Association between Two Variables.Measuring the Agreement between Two Variables.PART VIII: GETTING INTO A RELATIONSHIP.Straight-line Models: Linear Regression.Curvy Models: Logistic Regression.Appendix: Table of Random Numbers.Bibliography.Index.
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