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Fundamentals of Biostatistics

ISBN-10: 0534418201
ISBN-13: 9780534418205
Edition: 6th 2006
Authors: Bernard Rosner
List price: $332.95
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Description: FUNDAMENTALS OF BIOSTATISTICS (WITH CD-ROM) leads you through the methods, techniques, and computations necessary for success in the medical field. Every new concept is developed systematically through completely worked out examples from current  More...

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Book details

List price: $332.95
Edition: 6th
Copyright year: 2006
Publisher: Brooks/Cole
Publication date: 2/24/2005
Binding: Hardcover
Pages: 896
Size: 8.00" wide x 9.50" long x 1.75" tall
Weight: 4.004
Language: English

FUNDAMENTALS OF BIOSTATISTICS (WITH CD-ROM) leads you through the methods, techniques, and computations necessary for success in the medical field. Every new concept is developed systematically through completely worked out examples from current medical research problems.

Bernard Rosner is Professor in the Department of Medicine, Harvard Medical School, and the Department of Biostatistics at the Harvard School of Public Health. Dr. Rosner's research activities currently include longitudinal data analysis, analysis of clustered continuous, binary and ordinal data, methods for the adjustment of regression models for measurement error, and modeling of cancer incidence data.

General Overview
References
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
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
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
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
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
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
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
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
Hypothesis Testing: Categorical Data
Introduction
Two-Sample Test for Binomial Proportions
Fisher''s Exact Test
Two-Sample Test

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