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Record Nr. |
UNINA9910139197303321 |
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Autore |
Woolson Robert F |
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Titolo |
Statistical methods for the analysis of biomedical data [[electronic resource] /] / Robert F. Woolson, William R. Clarke |
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Pubbl/distr/stampa |
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New York, : Wiley-Interscience, c2002 |
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ISBN |
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1-282-25345-X |
9786613814104 |
1-118-03305-1 |
1-118-03130-X |
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Edizione |
[2nd ed.] |
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Descrizione fisica |
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1 online resource (714 p.) |
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Collana |
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Wiley series in probability and statistics |
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Altri autori (Persone) |
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ClarkeWilliam R (William Radue) |
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Disciplina |
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Soggetti |
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Medical statistics |
Biometry |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographies and index. |
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Nota di contenuto |
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Statistical Methods for the Analysis of Biomedical Data; Dedication; Contents; Preface to the 1987 Edition; Preface to the 2002 Edition; Acknowledgments; 1 Introduction; 1.1 Overview of Statistics; 1.2 A Designed Experiment; 1.2.1 Order of Interviewing (Randomization); 1.2.2 Possible Outcomes of the Experiment (Sample Space); 1.3 Scope and Organization of Book; References; 2 Descriptive Statistics; 2.1 Introduction; 2.2 Classification of Variables; 2.3 Representing Data with Notation; 2.4 Central Tendency of a Set of Data; 2.5 Variability in a Set of Data; 2.6 Pictorial Data Representation |
2.7 Sample Description with Grouped Data2.8 Tabulation and Graphing of Grouped Data; 2.9 Summary Statistics for Grouped Data; 2.10 Using SAS for Computations; 2.11 Summary; Problems; References; 3 Basic Probability Concepts; 3.1 Introduction; 3.2 Probability; 3.2.1 Probability Defined; 3.2.2 Addition Rule; 3.2.3 Conditional Probability and Multiplication Rule; 3.3 Bayes' Theorem: A Useful Result from Probability Theory; 3.4 Probability Distributions and Random Variables; 3.5 Summary; Problems; References; 4 Further Aspects of Probability; |
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4.1 Introduction |
4.2 Populations, Samples, and Random Samples4.3 Parameters and Statistics; 4.4 Permutations and Combinations: Factorial Notation; 4.5 Some Discrete Probability Distributions; 4.5.1 Binomial Distribution; 4.5.2 Poisson Distribution; 4.5.3 Hypergeometric Distribution; 4.5.4 Multinomial Distribution; 4.6 Normal Probability Distribution; 4.7 Sampling Distributions: Probability Distributions Generated by Random Sampling; 4.8 The t, χ2, and F Probability Distributions; 4.9 Summary; Problems; References; 5 Confidence Intervals and Hypothesis Testing: General Considerations and Applications |
5.1 Introduction5.2 Estimation of Population Characteristics: Point and Interval Estimation; 5.2.1 Confidence Interval for a Population Mean μ with Variance σ2 Known; 5.2.2 Confidence Interval for a Population Mean μ with Variance σ2 Unknown; 5.2.3 Confidence Interval for the Variance σ2 of a Normal Population; 5.2.4 Confidence Interval for a Binomial Proportion p; 5.3 Testing Statistical Hypotheses; 5.3.1 Hypothesis Testing for a Population Mean μ σ2 Known; 5.3.2 Hypothesis Testing for a Population Mean μ σ2 Unknown; 5.3.3 Hypothesis Testing for a Normal Population Variance σ2 |
5.3.4 Hypothesis Testing for Binomial Parameter p5.4 Using SAS for Computations; 5.5 Summary; Problems; References; 6 Comparison of Two Groups: t-Tests and Rank Tests; 6.1 Introduction; 6.2 Use of t-Tests for Group Comparisons; 6.2.1 Paired t-Test for Comparing Means: A Test for Matched Pairs; 6.2.2 Two-Sample t-Test for Comparing Means: A Test for Two Independent Groups; 6.2.3 Cochran-Cox t-Test for Equality of Means: A Modified t-Test for Two Independent Groups; 6.2.4 The F-Test for Equality of Variances: A Test for Two Independent Groups; 6.2.5 Transformation of Data to Equalize Variance |
6.3 Use of Rank Tests for Group Comparisons |
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Sommario/riassunto |
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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. |
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