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Principles of applied statistics

Author: D R Cox; Christl A Donnelly
Publisher: Cambridge, UK ; New York : Cambridge University Press, 2011.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
"Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation,
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Cox, D.R. (David Roxbee).
Principles of applied statistics.
Cambridge, UK ; New York : Cambridge University Press, 2011
(DLC) 2011023677
(OCoLC)727702115
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: D R Cox; Christl A Donnelly
ISBN: 9781139128797 1139128795 1139115960 9781139115964 9781139118132 1139118137 9781139005036 1139005030
OCLC Number: 768770719
Description: 1 online resource (x, 202 pages) : illustrations
Contents: Cover; Title; Copyright; Contents; Preface; 1 Some general concepts; 1.1 Preliminaries; 1.2 Components of investigation; 1.3 Aspects of study design; 1.4 Relationship between design and analysis; 1.5 Experimental and observational studies; 1.6 Principles of measurement; 1.7 Types and phases of analysis; 1.8 Formal analysis; 1.9 Probability models; 1.10 Prediction; 1.11 Synthesis; Notes; 2 Design of studies; 2.1 Introduction; 2.2 Unit of analysis; 2.3 Types of study; 2.4 Avoidance of systematic error; 2.5 Control and estimation of random error; 2.6 Scale of effort; 2.7 Factorial principle. Notes3 Special types of study; 3.1 Preliminaries; 3.2 Sampling a specific population; 3.2.1 Sampling frame; 3.2.2 Precision enhancement; 3.2.3 Multi-stage and temporal sampling; 3.2.4 Less standard sampling methods; 3.3 Experiments; 3.3.1 Primary formulation; 3.3.2 Precision improvement; 3.3.3 Factorial experiments; 3.3.4 Developments; 3.4 Cross-sectional observational study; 3.5 Prospective observational study; 3.6 Retrospective observational study; Notes; 4 Principles of measurement; 4.1 Criteria for measurements; 4.2 Classification of measurements; 4.3 Scale properties. 4.4 Classification by purpose4.5 Censoring; 4.6 Derived variables; 4.7 Latent variables; 4.7.1 Generalities; 4.7.2 Role in model formulation; 4.7.3 Latent structure and latent class models; 4.7.4 Measurement error in regression; Notes; 5 Preliminary analysis; 5.1 Introduction; 5.2 Data auditing; 5.3 Data screening; 5.4 Preliminary graphical analysis; 5.5 Preliminary tabular analysis; 5.6 More specialized measurement; 5.7 Discussion; 6 Model formulation; 6.1 Preliminaries; 6.2 Nature of probability models; 6.3 Types of model; 6.4 Interpretation of probability; 6.5 Empirical models. 6.5.1 Generalities6.5.2 Systematic variation; 6.5.3 Variational structure; 6.5.4 Unit of analysis; Notes; 7 Model choice; 7.1 Criteria for parameters; 7.1.1 Preliminaries; 7.1.2 Parameters of interest; 7.2 Nonspecific effects; 7.2.1 Preliminaries; 7.2.2 Stable treatment effect; 7.2.3 Unstable effect; 7.3 Choice of a specific model; Notes; 8 Techniques of formal inference; 8.1 Preliminaries; 8.2 Confidence limits; 8.3 Posterior distributions; 8.4 Significance tests; 8.4.1 Types of null hypothesis; 8.4.2 Test of atomic null hypothesis; 8.4.3 Application and interpretation of p-values. 8.4.4 Simulation-based procedures8.4.5 Tests of model adequacy; 8.4.6 Tests of model simplification; 8.5 Large numbers of significance tests; 8.5.1 Generalities; 8.5.2 Formulation; 8.5.3 Multi-stage formulation; 8.5.4 Bonferroni correction; 8.5.5 False discovery rate; 8.5.6 Empirical Bayes formulation; 8.6 Estimates and standard errors; 8.6.1 A final assessment; Notes; 9 Interpretation; 9.1 Introduction; 9.2 Statistical causality; 9.2.1 Preliminaries; 9.2.2 Causality and randomized experiments; 9.2.3 Observational parallel; 9.2.4 Qualitative guidelines; 9.2.5 A further notion.
Responsibility: D.R. Cox, Christl A. Donnelly.
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This compact package delivers decades of usable scientific experience. Cox and Donnelly lay out the strategic thinking that characterises the successful application of statistics, and how this  Read more...

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