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Link de la búsquedaAdvances in Statistical Methods for the Health Sciences / SpringerLink (Online service) ; Jean-Louis Auget ; Nagraj Balakrishnan ; Mesbah, Mounir ; Molenberghs, Geert (2007)
Título : Advances in Statistical Methods for the Health Sciences : Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Jean-Louis Auget ; Nagraj Balakrishnan ; Mesbah, Mounir ; Molenberghs, Geert Editorial: Boston, MA : Birkhäuser Boston Fecha de publicación: 2007 Colección: Statistics for Industry and Technology, ISSN 2364-6241 Número de páginas: XLII, 540 p Il.: online resource ISBN/ISSN/DL: 978-0-8176-4542-7 Idioma : Inglés (eng) Palabras clave: Mathematics Applied mathematics Engineering Probabilities Statistics Probability Theory and Stochastic Processes Applications of for Life Sciences, Medicine, Health Sciences Statistical Methods Clasificación: 51 Matemáticas Resumen: Statistical methods have become increasingly important and now form integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained volume, an outgrowth of an "International Conference on Statistical Methods in Health Sciences," covers a wide range of topics pertaining to new statistical methods and novel applications in the health sciences. The chapters, written by leading experts in their respective fields, are thematically divided into the following areas: * Prognostic studies and general epidemiology * Pharmacovigilance * Quality of life * Survival analysis * Clustering * Safety and efficacy assessment * Clinical design * Models for the environment * Genomic analysis * Animal health This comprehensive volume will be highly useful an of great interest to the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics. Nota de contenido: Prognostic Studies and General Epidemiology -- Systematic Review of Multiple Studies of Prognosis: The Feasibility of Obtaining Individual Patient Data -- On Statistical Approaches for the Multivariable Analysis of Prognostic Marker Studies -- Where Next for Evidence Synthesis of Prognostic Marker Studies? Improving the Quality and Reporting of Primary Studies to Facilitate Clinically Relevant Evidence-Based Results -- Pharmacovigilance -- Sentinel Event Methods for Monitoring Unanticipated Adverse Events -- Spontaneous Reporting System Modelling for the Evaluation of Automatic Signal Generation Methods in Pharmacovigilance -- Quality of Life -- Latent Covariates in Generalized Linear Models: A Rasch Model Approach -- Sequential Analysis of Quality of Life Measurements with the Mixed Partial Credit Model -- A Parametric Degradation Model Used in Reliability, Survival Analysis, and Quality of Life -- Agreement Between Two Ratings with Different Ordinal Scales -- Survival Analysis -- The Role of Correlated Frailty Models in Studies of Human Health, Ageing, and Longevity -- Prognostic Factors and Prediction of Residual Survival for Hospitalized Elderly Patients -- New Models and Methods for Survival Analysis of Experimental Data -- Uniform Consistency for Conditional Lifetime Distribution Estimators Under Random Right-Censorship -- Sequential Estimation for the Semiparametric Additive Hazard Model -- Variance Estimation of a Survival Function with Doubly Censored Failure Time Data -- Clustering -- Statistical Models and Artificial Neural Networks: Supervised Classification and Prediction Via Soft Trees -- Multilevel Clustering for Large Databases -- Neural Networks: An Application for Predicting Smear Negative Pulmonary Tuberculosis -- Assessing Drug Resistance in HIV Infection Using Viral Load Using Segmented Regression -- Assessment of Treatment Effects on HIV Pathogenesis Under Treatment By State Space Models -- Safety and Efficacy Assessment -- Safety Assessment Versus Efficacy Assessment -- Cancer Clinical Trials with Efficacy and Toxicity Endpoints: A Simulation Study to Compare Two Nonparametric Methods -- Safety Assessment in Pilot Studies When Zero Events Are Observed -- Clinical Designs -- An Assessment of Up-and-Down Designs and Associated Estimators in Phase I Trials -- Design of Multicentre Clinical Trials with Random Enrolment -- Statistical Methods for Combining Clinical Trial Phases II And III -- SCPRT: A Sequential Procedure That Gives Another Reason to Stop Clinical Trials Early -- Models for the Environment -- Seasonality Assessment for Biosurveillance Systems -- Comparison of Three Convolution Prior Spatial Models for Cancer Incidence -- Longitudinal Analysis of Short-Term Bronchiolitis Air Pollution Association Using Semiparametric Models -- Genomic Analysis -- Are There Correlated Genomic Substitutions? -- Animal Health -- Swiss Federal Veterinary Office Risk Assessments: Advantages and Limitations of The Qualitative Method -- Qualitative Risk Analysis in Animal Health: A Methodological Example En línea: http://dx.doi.org/10.1007/978-0-8176-4542-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34547 Advances in Statistical Methods for the Health Sciences : Applications to Cancer and AIDS Studies, Genome Sequence Analysis, and Survival Analysis [documento electrónico] / SpringerLink (Online service) ; Jean-Louis Auget ; Nagraj Balakrishnan ; Mesbah, Mounir ; Molenberghs, Geert . - Boston, MA : Birkhäuser Boston, 2007 . - XLII, 540 p : online resource. - (Statistics for Industry and Technology, ISSN 2364-6241) .
ISBN : 978-0-8176-4542-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Applied mathematics Engineering Probabilities Statistics Probability Theory and Stochastic Processes Applications of for Life Sciences, Medicine, Health Sciences Statistical Methods Clasificación: 51 Matemáticas Resumen: Statistical methods have become increasingly important and now form integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained volume, an outgrowth of an "International Conference on Statistical Methods in Health Sciences," covers a wide range of topics pertaining to new statistical methods and novel applications in the health sciences. The chapters, written by leading experts in their respective fields, are thematically divided into the following areas: * Prognostic studies and general epidemiology * Pharmacovigilance * Quality of life * Survival analysis * Clustering * Safety and efficacy assessment * Clinical design * Models for the environment * Genomic analysis * Animal health This comprehensive volume will be highly useful an of great interest to the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics. Nota de contenido: Prognostic Studies and General Epidemiology -- Systematic Review of Multiple Studies of Prognosis: The Feasibility of Obtaining Individual Patient Data -- On Statistical Approaches for the Multivariable Analysis of Prognostic Marker Studies -- Where Next for Evidence Synthesis of Prognostic Marker Studies? Improving the Quality and Reporting of Primary Studies to Facilitate Clinically Relevant Evidence-Based Results -- Pharmacovigilance -- Sentinel Event Methods for Monitoring Unanticipated Adverse Events -- Spontaneous Reporting System Modelling for the Evaluation of Automatic Signal Generation Methods in Pharmacovigilance -- Quality of Life -- Latent Covariates in Generalized Linear Models: A Rasch Model Approach -- Sequential Analysis of Quality of Life Measurements with the Mixed Partial Credit Model -- A Parametric Degradation Model Used in Reliability, Survival Analysis, and Quality of Life -- Agreement Between Two Ratings with Different Ordinal Scales -- Survival Analysis -- The Role of Correlated Frailty Models in Studies of Human Health, Ageing, and Longevity -- Prognostic Factors and Prediction of Residual Survival for Hospitalized Elderly Patients -- New Models and Methods for Survival Analysis of Experimental Data -- Uniform Consistency for Conditional Lifetime Distribution Estimators Under Random Right-Censorship -- Sequential Estimation for the Semiparametric Additive Hazard Model -- Variance Estimation of a Survival Function with Doubly Censored Failure Time Data -- Clustering -- Statistical Models and Artificial Neural Networks: Supervised Classification and Prediction Via Soft Trees -- Multilevel Clustering for Large Databases -- Neural Networks: An Application for Predicting Smear Negative Pulmonary Tuberculosis -- Assessing Drug Resistance in HIV Infection Using Viral Load Using Segmented Regression -- Assessment of Treatment Effects on HIV Pathogenesis Under Treatment By State Space Models -- Safety and Efficacy Assessment -- Safety Assessment Versus Efficacy Assessment -- Cancer Clinical Trials with Efficacy and Toxicity Endpoints: A Simulation Study to Compare Two Nonparametric Methods -- Safety Assessment in Pilot Studies When Zero Events Are Observed -- Clinical Designs -- An Assessment of Up-and-Down Designs and Associated Estimators in Phase I Trials -- Design of Multicentre Clinical Trials with Random Enrolment -- Statistical Methods for Combining Clinical Trial Phases II And III -- SCPRT: A Sequential Procedure That Gives Another Reason to Stop Clinical Trials Early -- Models for the Environment -- Seasonality Assessment for Biosurveillance Systems -- Comparison of Three Convolution Prior Spatial Models for Cancer Incidence -- Longitudinal Analysis of Short-Term Bronchiolitis Air Pollution Association Using Semiparametric Models -- Genomic Analysis -- Are There Correlated Genomic Substitutions? -- Animal Health -- Swiss Federal Veterinary Office Risk Assessments: Advantages and Limitations of The Qualitative Method -- Qualitative Risk Analysis in Animal Health: A Methodological Example En línea: http://dx.doi.org/10.1007/978-0-8176-4542-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34547 Ejemplares
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Título : Chemometrics with R : Multivariate Data Analysis in the Natural Sciences and Life Sciences Tipo de documento: documento electrónico Autores: Wehrens, Ron ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2011 Colección: Use R Número de páginas: XIV, 286 p. 99 illus Il.: online resource ISBN/ISSN/DL: 978-3-642-17841-2 Idioma : Inglés (eng) Palabras clave: Life sciences Chemoinformatics Bioinformatics Computational biology Statistics Sciences Computer Applications in Chemistry for Sciences, Medicine, Health Appl. Clasificación: 51 Matemáticas Resumen: "Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R Nota de contenido: Introduction -- Part I Preliminaries: Data -- Preprocessing -- Part II Exploratory Analysis: Principal Component Analysis -- Self-Organizing Maps -- Clustering -- Part III Modelling: Classification -- Multivariate Regression -- Part IV Model Inspection: Validation -- Variable Selection -- Part V Applications: Chemometric -- Part VI Appendices: R packages Used in This Book -- References -- Index En línea: http://dx.doi.org/10.1007/978-3-642-17841-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33405 Chemometrics with R : Multivariate Data Analysis in the Natural Sciences and Life Sciences [documento electrónico] / Wehrens, Ron ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2011 . - XIV, 286 p. 99 illus : online resource. - (Use R) .
ISBN : 978-3-642-17841-2
Idioma : Inglés (eng)
Palabras clave: Life sciences Chemoinformatics Bioinformatics Computational biology Statistics Sciences Computer Applications in Chemistry for Sciences, Medicine, Health Appl. Clasificación: 51 Matemáticas Resumen: "Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R Nota de contenido: Introduction -- Part I Preliminaries: Data -- Preprocessing -- Part II Exploratory Analysis: Principal Component Analysis -- Self-Organizing Maps -- Clustering -- Part III Modelling: Classification -- Multivariate Regression -- Part IV Model Inspection: Validation -- Variable Selection -- Part V Applications: Chemometric -- Part VI Appendices: R packages Used in This Book -- References -- Index En línea: http://dx.doi.org/10.1007/978-3-642-17841-2 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33405 Ejemplares
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Título : Excel 2007 for Biological and Life Sciences Statistics : A Guide to Solving Practical Problems Tipo de documento: documento electrónico Autores: Quirk, Thomas J ; SpringerLink (Online service) ; Quirk, Meghan ; Horton, Howard Editorial: New York, NY : Springer New York Fecha de publicación: 2013 Otro editor: Imprint: Springer Número de páginas: XVII, 232 p. 162 illus., 146 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-6003-9 Idioma : Inglés (eng) Palabras clave: Statistics for Life Sciences, Medicine, Health Sciences and Computing/Statistics Programs Statistics, general Clasificación: 51 Matemáticas Resumen: This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2007 for Biological and Life Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned. n Includes 162 illustrations in color n Suitable for undergraduates or graduate students Nota de contenido: Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- Random Number Generator -- Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- One-Group t-Test for the Mean -- Two-Group t-Test of the Difference of the Means for Independent Groups -- Correlation and Simple Linear Regression -- Multiple Correlation and Multiple Regression -- One-Way Analysis of Variance (ANOVA) -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-table -- Index En línea: http://dx.doi.org/10.1007/978-1-4614-6003-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32283 Excel 2007 for Biological and Life Sciences Statistics : A Guide to Solving Practical Problems [documento electrónico] / Quirk, Thomas J ; SpringerLink (Online service) ; Quirk, Meghan ; Horton, Howard . - New York, NY : Springer New York : Imprint: Springer, 2013 . - XVII, 232 p. 162 illus., 146 illus. in color : online resource.
ISBN : 978-1-4614-6003-9
Idioma : Inglés (eng)
Palabras clave: Statistics for Life Sciences, Medicine, Health Sciences and Computing/Statistics Programs Statistics, general Clasificación: 51 Matemáticas Resumen: This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2007 for Biological and Life Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned. n Includes 162 illustrations in color n Suitable for undergraduates or graduate students Nota de contenido: Sample Size, Mean, Standard Deviation, and Standard Error of the Mean -- Random Number Generator -- Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing -- One-Group t-Test for the Mean -- Two-Group t-Test of the Difference of the Means for Independent Groups -- Correlation and Simple Linear Regression -- Multiple Correlation and Multiple Regression -- One-Way Analysis of Variance (ANOVA) -- Appendix A: Answers to End-of-Chapter Practice Problems -- Appendix B: Practice Test -- Appendix C: Answers to Practice Test -- Appendix D: Statistical Formulas -- Appendix E: t-table -- Index En línea: http://dx.doi.org/10.1007/978-1-4614-6003-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32283 Ejemplares
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Título : Excel 2010 for Biological and Life Sciences Statistics : A Guide to Solving Practical Problems Tipo de documento: documento electrónico Autores: Quirk, Thomas J ; SpringerLink (Online service) ; Quirk, Meghan ; Horton, Howard Editorial: New York, NY : Springer New York Fecha de publicación: 2013 Otro editor: Imprint: Springer Número de páginas: XVII, 236 p. 162 illus., 160 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-5779-4 Idioma : Inglés (eng) Palabras clave: Statistics for Life Sciences, Medicine, Health Sciences and Computing/Statistics Programs Statistics, general Clasificación: 51 Matemáticas Resumen: This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2010 for Biological and Life Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned. Includes 162 illustrations in color Suitable for undergraduates or graduate students En línea: http://dx.doi.org/10.1007/978-1-4614-5779-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32269 Excel 2010 for Biological and Life Sciences Statistics : A Guide to Solving Practical Problems [documento electrónico] / Quirk, Thomas J ; SpringerLink (Online service) ; Quirk, Meghan ; Horton, Howard . - New York, NY : Springer New York : Imprint: Springer, 2013 . - XVII, 236 p. 162 illus., 160 illus. in color : online resource.
ISBN : 978-1-4614-5779-4
Idioma : Inglés (eng)
Palabras clave: Statistics for Life Sciences, Medicine, Health Sciences and Computing/Statistics Programs Statistics, general Clasificación: 51 Matemáticas Resumen: This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2010 for Biological and Life Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned. Includes 162 illustrations in color Suitable for undergraduates or graduate students En línea: http://dx.doi.org/10.1007/978-1-4614-5779-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32269 Ejemplares
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Título : Historical Encyclopedia of Natural and Mathematical Sciences Tipo de documento: documento electrónico Autores: Ari Ben-Menahem ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2009 Número de páginas: eReference Il.: online resource ISBN/ISSN/DL: 978-3-540-68832-7 Idioma : Inglés (eng) Palabras clave: Mathematics Earth sciences Life Physics Environment Mathematics, general Sciences, Physics, Environment, Clasificación: 51 Matemáticas Resumen: This milestone extensive work combines the essentials of history – biography, chronology, political and economic background – with the observations, theories, principles, laws and equations that constitute the specifics of science. The 5800-page Encyclopedia arises from the conviction that the optimal perspective on science is through the lens of history, setting aside traditional divisions of discipline and specialty, and rising above geopolitical boundaries. Reaching from 4,200 BCE to the 21st century CE, the Encyclopedia relates (as the author himself puts it) "not only who did it and when it was done but also precisely what was done." The author, Ari Ben-Menahem, surveys 100 generations of great thinkers, offering 2070 detailed biographies of scientists, engineers, explorers and inventors, who left their mark on the history of science and technology. The span of coverage is all-encompassing: mathematics, philosophy, logic, physical and environmental sciences (including physics, chemistry, astronomy, earth and space sciences and cosmology), life sciences (biology, medicine, physiology, botany, zoology and biochemistry), associated engineering disciplines, and the social sciences (among them economics, psychology, sociology, anthropology, linguistics and more). The six-volume Encyclopedia also includes 380 articles summarizing the time-line of ideas in the leading fields of science, technology, mathematics and philosophy, plus useful tables, figures and photos, and 20 ‘Science Progress Reports’ detailing scientific setbacks. Interspersed throughout are quotations, gathered from the wit and wisdom of sages, savants and scholars throughout the ages from antiquity to modern times En línea: http://dx.doi.org/10.1007/978-3-540-68832-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34013 Historical Encyclopedia of Natural and Mathematical Sciences [documento electrónico] / Ari Ben-Menahem ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2009 . - eReference : online resource.
ISBN : 978-3-540-68832-7
Idioma : Inglés (eng)
Palabras clave: Mathematics Earth sciences Life Physics Environment Mathematics, general Sciences, Physics, Environment, Clasificación: 51 Matemáticas Resumen: This milestone extensive work combines the essentials of history – biography, chronology, political and economic background – with the observations, theories, principles, laws and equations that constitute the specifics of science. The 5800-page Encyclopedia arises from the conviction that the optimal perspective on science is through the lens of history, setting aside traditional divisions of discipline and specialty, and rising above geopolitical boundaries. Reaching from 4,200 BCE to the 21st century CE, the Encyclopedia relates (as the author himself puts it) "not only who did it and when it was done but also precisely what was done." The author, Ari Ben-Menahem, surveys 100 generations of great thinkers, offering 2070 detailed biographies of scientists, engineers, explorers and inventors, who left their mark on the history of science and technology. The span of coverage is all-encompassing: mathematics, philosophy, logic, physical and environmental sciences (including physics, chemistry, astronomy, earth and space sciences and cosmology), life sciences (biology, medicine, physiology, botany, zoology and biochemistry), associated engineering disciplines, and the social sciences (among them economics, psychology, sociology, anthropology, linguistics and more). The six-volume Encyclopedia also includes 380 articles summarizing the time-line of ideas in the leading fields of science, technology, mathematics and philosophy, plus useful tables, figures and photos, and 20 ‘Science Progress Reports’ detailing scientific setbacks. Interspersed throughout are quotations, gathered from the wit and wisdom of sages, savants and scholars throughout the ages from antiquity to modern times En línea: http://dx.doi.org/10.1007/978-3-540-68832-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34013 Ejemplares
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