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Añadir al carritoTaschenbuch. Condición: Neu. Advanced Statistical Methods in Life Science | Basavarajaiah D. M (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | Chapman and Hall/CRC | EAN 9781032713823 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu.
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ISBN 10: 1032713828 ISBN 13: 9781032713823
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in life sciences. Advanced statistical methods, such as testing of hypotheses, recent methods of sample size determination/imputation, estimation techniques, probability distributions, and univariate analysis demonstrated with real data, and their integration into life sciences are included in this book. Advanced topics are presented with sufficient conceptual depth and examples to explain the use of recent statistical techniques and to demonstrate what conclusions can be drawn at the right time using modeling in life science research.Key features:Explains the derivation of statistical models to prove disease transmission using massive real-world datasets to explore practical applicabilityIncorporates the application of innovative advanced statistical and epidemiological models and demonstrates the possible solutions for public health policy interventionHelps to understand the process of hypothesis testing in small or larger observations by using weighted parametersPresents suitable examples and real-life research datasets, and all models can easily be followed in formulating statistical and mathematical derivations and key pointsIncludes machine learning (ML), statistical methods for meta-analysis, testing of hypotheses, methods of imputation, estimation techniques, probability distributions, univariate analysis, and recent nonparametric methods, all illustrated through actual dataThis textbook is for students and scholars of various courses in life sciences, medicine, mathematics, and statistical science. It will also help academicians and researchers to understand the foundation of this topic. 350 pp. Englisch.
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Basavarajaiah D.M is currently the Head of the Department of Statistics and Computer Science at Karnataka Veterinary, Animal, and Fisheries Sciences University (B), Hebbal, Bangalore. He obtained his Ph.D. from the National Institute of .
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Añadir al carritoPaperback. Condición: new. Paperback. This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in life sciences. Advanced statistical methods, such as testing of hypotheses, recent methods of sample size determination/imputation, estimation techniques, probability distributions, and univariate analysis demonstrated with real data, and their integration into life sciences are included in this book. Advanced topics are presented with sufficient conceptual depth and examples to explain the use of recent statistical techniques and to demonstrate what conclusions can be drawn at the right time using modeling in life science research.Key features:Explains the derivation of statistical models to prove disease transmission using massive real-world datasets to explore practical applicabilityIncorporates the application of innovative advanced statistical and epidemiological models and demonstrates the possible solutions for public health policy interventionHelps to understand the process of hypothesis testing in small or larger observations by using weighted parametersPresents suitable examples and real-life research datasets, and all models can easily be followed in formulating statistical and mathematical derivations and key pointsIncludes machine learning (ML), statistical methods for meta-analysis, testing of hypotheses, methods of imputation, estimation techniques, probability distributions, univariate analysis, and recent nonparametric methods, all illustrated through actual dataThis textbook is for students and scholars of various courses in life sciences, medicine, mathematics, and statistical science. It will also help academicians and researchers to understand the foundation of this topic. This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in Life sciences. Advanced statistical methods like testing of hypotheses, etc. as demonstrated by real data, and their integration into life sciences are included in the book. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in life sciences. Advanced statistical methods, such as testing of hypotheses, recent methods of sample size determination/imputation, estimation techniques, probability distributions, and univariate analysis demonstrated with real data, and their integration into life sciences are included in this book. Advanced topics are presented with sufficient conceptual depth and examples to explain the use of recent statistical techniques and to demonstrate what conclusions can be drawn at the right time using modeling in life science research.Key features:Explains the derivation of statistical models to prove disease transmission using massive real-world datasets to explore practical applicabilityIncorporates the application of innovative advanced statistical and epidemiological models and demonstrates the possible solutions for public health policy interventionHelps to understand the process of hypothesis testing in small or larger observations by using weighted parametersPresents suitable examples and real-life research datasets, and all models can easily be followed in formulating statistical and mathematical derivations and key pointsIncludes machine learning (ML), statistical methods for meta-analysis, testing of hypotheses, methods of imputation, estimation techniques, probability distributions, univariate analysis, and recent nonparametric methods, all illustrated through actual dataThis textbook is for students and scholars of various courses in life sciences, medicine, mathematics, and statistical science. It will also help academicians and researchers to understand the foundation of this topic.
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Añadir al carritoPaperback. Condición: new. Paperback. This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in life sciences. Advanced statistical methods, such as testing of hypotheses, recent methods of sample size determination/imputation, estimation techniques, probability distributions, and univariate analysis demonstrated with real data, and their integration into life sciences are included in this book. Advanced topics are presented with sufficient conceptual depth and examples to explain the use of recent statistical techniques and to demonstrate what conclusions can be drawn at the right time using modeling in life science research.Key features:Explains the derivation of statistical models to prove disease transmission using massive real-world datasets to explore practical applicabilityIncorporates the application of innovative advanced statistical and epidemiological models and demonstrates the possible solutions for public health policy interventionHelps to understand the process of hypothesis testing in small or larger observations by using weighted parametersPresents suitable examples and real-life research datasets, and all models can easily be followed in formulating statistical and mathematical derivations and key pointsIncludes machine learning (ML), statistical methods for meta-analysis, testing of hypotheses, methods of imputation, estimation techniques, probability distributions, univariate analysis, and recent nonparametric methods, all illustrated through actual dataThis textbook is for students and scholars of various courses in life sciences, medicine, mathematics, and statistical science. It will also help academicians and researchers to understand the foundation of this topic. This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in Life sciences. Advanced statistical methods like testing of hypotheses, etc. as demonstrated by real data, and their integration into life sciences are included in the book. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Añadir al carritoPaperback. Condición: new. Paperback. This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in life sciences. Advanced statistical methods, such as testing of hypotheses, recent methods of sample size determination/imputation, estimation techniques, probability distributions, and univariate analysis demonstrated with real data, and their integration into life sciences are included in this book. Advanced topics are presented with sufficient conceptual depth and examples to explain the use of recent statistical techniques and to demonstrate what conclusions can be drawn at the right time using modeling in life science research.Key features:Explains the derivation of statistical models to prove disease transmission using massive real-world datasets to explore practical applicabilityIncorporates the application of innovative advanced statistical and epidemiological models and demonstrates the possible solutions for public health policy interventionHelps to understand the process of hypothesis testing in small or larger observations by using weighted parametersPresents suitable examples and real-life research datasets, and all models can easily be followed in formulating statistical and mathematical derivations and key pointsIncludes machine learning (ML), statistical methods for meta-analysis, testing of hypotheses, methods of imputation, estimation techniques, probability distributions, univariate analysis, and recent nonparametric methods, all illustrated through actual dataThis textbook is for students and scholars of various courses in life sciences, medicine, mathematics, and statistical science. It will also help academicians and researchers to understand the foundation of this topic. This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in Life sciences. Advanced statistical methods like testing of hypotheses, etc. as demonstrated by real data, and their integration into life sciences are included in the book. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.