Principles of applied statistics
(eBook)
Author:
Contributors:
Donnelly, Christl A., author.
Published:
Cambridge, UK ; New York : Cambridge University Press, 2011.
Format:
eBook
ISBN:
9781139128797, 1139128795, 1139115960, 9781139115964, 9781139118132, 1139118137, 9781139005036, 1139005030, 1139235109, 9781139235105, 1107229561, 9781107229563, 1283296462, 9781283296465, 9786613296467, 6613296465, 1139123882, 9781139123884, 1139113771, 9781139113779
Physical Desc:
1 online resource (x, 202 pages) : illustrations
Status:
Ebsco (CCU)
Description
"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, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work"--
"In ideal sequence is defined specifying the progression of an investigation from the conception of one or more research questions to the drawing of conclusions. The role of statistical analysis is outlined for design, measurement, analysis and interpretation. 1.1 Preliminaries This short chapter gives a general account of the issues to be discussed in the book, namely those connected with situations in which appreciable unexplained and haphazard variation is present. We outline in idealized form the main phases of this kind of scientific investigation and the stages of statistical analysis likely to be needed. It would be arid to attempt a precise definition of statistical analysis as contrasted with other forms of analysis"--
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Ebsco (CCU)
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Citations
APA Citation (style guide)
Cox, D. R., & Donnelly, C. A. (2011). Principles of applied statistics. Cambridge, UK ; New York, Cambridge University Press.
Chicago / Turabian - Author Date Citation (style guide)Cox, D. R and Christl A., Donnelly. 2011. Principles of Applied Statistics. Cambridge, UK ; New York, Cambridge University Press.
Chicago / Turabian - Humanities Citation (style guide)Cox, D. R and Christl A., Donnelly, Principles of Applied Statistics. Cambridge, UK ; New York, Cambridge University Press, 2011.
MLA Citation (style guide)Cox, D. R. and Christl A. Donnelly. Principles of Applied Statistics. Cambridge, UK ; New York, Cambridge University Press, 2011.
Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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Language:
English
Notes
Bibliography
Includes bibliographical references (pages 189-197) and index.
Description
"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, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work"--,Provided by publisher
Description
"In ideal sequence is defined specifying the progression of an investigation from the conception of one or more research questions to the drawing of conclusions. The role of statistical analysis is outlined for design, measurement, analysis and interpretation. 1.1 Preliminaries This short chapter gives a general account of the issues to be discussed in the book, namely those connected with situations in which appreciable unexplained and haphazard variation is present. We outline in idealized form the main phases of this kind of scientific investigation and the stages of statistical analysis likely to be needed. It would be arid to attempt a precise definition of statistical analysis as contrasted with other forms of analysis"--,Provided by publisher
Language
English.
Staff View
Grouped Work ID:
45cad172-c58c-9104-09db-14af4dea1651
Record Information
| Last File Modification Time | Apr 05, 2024 09:29:46 PM |
|---|---|
| Last Grouped Work Modification Time | Apr 05, 2024 09:12:39 PM |
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| 245 | 1 | 0 | |a Principles of applied statistics /|c D.R. Cox, Christl A. Donnelly. |
| 260 | |a Cambridge, UK ;|a New York :|b Cambridge University Press,|c 2011. | ||
| 300 | |a 1 online resource (x, 202 pages) :|b illustrations | ||
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| 520 | |a "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, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work"--|c Provided by publisher | ||
| 520 | |a "In ideal sequence is defined specifying the progression of an investigation from the conception of one or more research questions to the drawing of conclusions. The role of statistical analysis is outlined for design, measurement, analysis and interpretation. 1.1 Preliminaries This short chapter gives a general account of the issues to be discussed in the book, namely those connected with situations in which appreciable unexplained and haphazard variation is present. We outline in idealized form the main phases of this kind of scientific investigation and the stages of statistical analysis likely to be needed. It would be arid to attempt a precise definition of statistical analysis as contrasted with other forms of analysis"--|c Provided by publisher | ||
| 504 | |a Includes bibliographical references (pages 189-197) and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
| 505 | 8 | |a 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. | |
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