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Fundamentals of biostatistics Bernard Rosner.

Por: Detalles de publicación: Belmont, CA Thomson-Brooks/Cole c2006.Edición: 6th edDescripción: xix, 868 p. ill. 25 cm. 1 CD-ROM (4 3/4 in.)ISBN:
  • 0534418201
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Bernard Rosner's FUNDAMENTALS OF BIOSTATISTICS is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through completely worked out examples from current medical research problems.

Accompanying CD-ROM contains a student study guide, and data sets in the formats of Minitab, SPSS, SAS, JMP, Excel, and ASCII.

Includes bibliographical references and index.

Tabla de contenidos provista por Syndetics

  • 1 General Overview
  • References
  • 2 Descriptive Statistics
  • Introduction
  • Measures of Location
  • Some Properties of the Arithmetic Mean
  • Measures of Spread
  • Some Properties of the Variance and Standard Deviation
  • The Coefficient of Variation
  • Grouped Data
  • Graphic Methods
  • Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
  • Case Study: Effects of Tobacco Use of Bone Mineral Density in Middle-Aged Women
  • Summary
  • Problems
  • References
  • 3 Probability
  • Introduction
  • Definition of Probability
  • Some Useful Probabilistic Notation
  • The Multiplication Law of Probability
  • The Addition Law of Probability
  • Conditional Probability
  • Bayes'' Rule and Screening Tests
  • Prevalence and Incidence
  • Summary
  • Problems
  • References
  • 4 Discrete Probability Distributions
  • Introduction
  • Random Variables
  • The Probability Mass Function for a Discrete Random Variable
  • The Expected Value of a Discrete Random Variable
  • The Variance of a Discrete Random Variable
  • The Cumulative-Distribution Function of a Discrete Random Variable
  • Permutations and Combinations
  • The Binomial Distribution
  • Expected Value and Variance of the Binomial Distribution
  • The Poisson Distribution
  • Computation of Poisson Probabilities
  • Expected Value and Variance of the Poisson Distribution
  • Poisson Approximation to the Binomial Distribution
  • Summary
  • Problems
  • References
  • 5 Continuous Probability Distributions
  • Introduction
  • General Concepts
  • The Normal Distribution
  • Properties of the Standard Normal Distribution
  • Conversion from an N([mean], [variance]) Distribution to an N(0, 1) Distribution
  • Linear Combinations of Random Variables
  • Normal Approximation to the Binomial Distribution
  • Normal Approximation to the Poisson Distribution
  • Summary
  • Problems
  • References
  • 6 Estimation
  • Introduction
  • The Relationship Between Population and Sample
  • Random-Number Tables
  • Randomized Clinical Trials
  • Estimation of the Mean of a Distribution
  • Case Study: Relationship of Cigarette Smoking to Bone Mineral Density (BMD) Among Middle-Aged Women
  • Estimation of the Variance of a Distribution
  • Estimation for the Binomial Distribution
  • Estimation for the Poisson Distribution
  • One-Sided Confidence Intervals
  • Summary
  • Problems
  • References
  • 7 Hypothesis Testing: One-Sample Inference
  • Introduction
  • General Concepts
  • One-Sample Test for the Mean of a Normal Distribution: One-Sided Alternatives
  • One-Sample Test for the Mean of a Normal Distribution: Two-Sided Alternatives
  • The Power of a Test
  • Sample-Size Determination
  • The Relationship Between Hypothesis Testing and Confidence Intervals
  • One-Sample Chi-Squared Test for the Variance of a Normal Distribution
  • One-Sample Test for a Binomial Proportion
  • One-Sample Inference for the Poisson Distribution
  • Case Study: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
  • Summary
  • Problems
  • References
  • 8 Hypothesis Testing: Two-Sample Inference
  • Introduction
  • The Paired t Test
  • Interval Estimation for the Comparison of Means from Two Paired Samples
  • Two-Sample t Test for Independent Samples with Equal Variances
  • Interval Estimation for the Comparison of Means from Two Independent Samples (Equal Variance Case)
  • Testing for the Equality of Two Variances
  • Two-Sample t Test for Independent Samples with Unequal Variances
  • Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
  • The Treatment of Outliers
  • Estimation of Sample Size and Power for Comparing Two Means
  • Sample-Size Estimation for Longitudinal Studies
  • Summary
  • Problems
  • References
  • 9 Nonparametric Methods
  • Introduction
  • The Sign Test
  • The Wilcoxon Signed-Rank Test
  • The Wilcoxon Rank-Sum Test
  • Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
  • Summary
  • Problems
  • References
  • 10 Hypothesis Testing: Categorical Data
  • Introduction
  • Two-Sample Test for Binomial Proportions
  • Fisher''s Exact Test
  • Two-Sample Test
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