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Synopsis

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 applicability
  • Incorporates the application of innovative advanced statistical and epidemiological models and demonstrates the possible solutions for public health policy intervention
  • Helps to understand the process of hypothesis testing in small or larger observations by using weighted parameters
  • Presents suitable examples and real-life research datasets, and all models can easily be followed in formulating statistical and mathematical derivations and key points
  • Includes 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 data

This 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.

"synopsis" may belong to another edition of this title.

About the Author

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 Epidemiology (NIE), ICMR, Chennai (affiliated with the University of Madras). His research focuses on statistical theory and statistical modeling of high‑dimensional datasets in agriculture, medicine, veterinary medicine, and animal sciences. He has authored 100 research articles and six academic books with reputed publishers, including works on HIV transmission statistical modeling, the design of experiments and advanced statistical techniques in clinical research, and COVID transmission modeling (published by CRC Press, UK). He serves as an editorial board member and scientific board advisor for various international indexed journals. He is a life member of numerous academic organizations and has received several accolades for his academic and research excellence. These include the Chartered Scientist award stalwart by the Science Council, the United Kingdom, in collaboration with the Royal Statistical Society; the Outstanding International Scientist award from VDGOOD organization; the Best Reviewer award (2016) from ‘TRANSSTELLAR’ Journal Publications and Research Consultancy, TJPRC Ltd. (NAAS‑rated journals); and fellowships from the Royal Statistical Society, UK (London) and the Mathematical Society, UK (London). He has been honored with the Bharathshikshratana and Indo‑Dubai Achiever’s Pacific awards by the Global Society of Health and Educational Growth, New Delhi. Other awards include Best Reviewer (2015), Best Scientific Board Advisor (2016), and Best Editorial and Researcher awards conferred by the International Academy of Engineering Science and Technology, USA. He is an active member of the Board of Studies and the Academic Council of various universities.

Narasimhamurthy B is a former Scientist ‘G’ (Director Grade cadre) at the National Institute of Epidemiology, ICMR, Chennai. Currently, he is an independent National Level Monitor for the National Health Mission, MOH&FW, Government of India. He obtained his Ph.D. from the International Institute of Population Science (IIPS), affiliated with Bombay University, in 1985. His areas of research include mathematical statistics, operational research, clinical research, public health, demography and vital statistics, and mathematical modeling in medical science and public health. He has authored more than 100 research articles published in reputed national and international journals and co‑authored four books, including HIV transmission statistical modeling, design of experiments and advanced statistical techniques in clinical research, and COVID transmission modeling (published by CRC Press, UK). He has also guided research scholars for their Ph.D. He has served as an editorial board member and scientific board advisor for various international MCI and UGC‑recognized journals and is a life member of various academic organizations. He has been honored with several accolades for his academic and research excellence, including the Prof. R. N. Srivastava Gold Medal Award, the Bharat Jyothi Award, the Bharat Ratna Indira Gandhi Gold Medal Award, and the Best Citizens of India award. Recently, he was recognized as one of the Asian Admirable Achievers. He serves as a member of the Board of Studies for various national universities, including the University of Madras, Acharya Nagarjuna University, and the University of Kerala. He is also a visiting emeritus professor at Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, and North Carolina University, USA, among others.

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Paperback. Condition: 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 the 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 data sets to explore practical applicability Incorporates application of innovative advanced statistical and epidemiological models and demonstrates possible solutions for public health policy intervention Helps to understand the process of hypothesis testing in small or larger observations by using weighted parameters Presents suitable examples and real-life research datasets, and all models can easily be followed in formulating the statistical and mathematical derivations and key points Includes machine learning (AI), 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 data.This 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032713823

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Paperback. Condition: 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 the 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 data sets to explore practical applicability Incorporates application of innovative advanced statistical and epidemiological models and demonstrates possible solutions for public health policy intervention Helps to understand the process of hypothesis testing in small or larger observations by using weighted parameters Presents suitable examples and real-life research datasets, and all models can easily be followed in formulating the statistical and mathematical derivations and key points Includes machine learning (AI), 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 data.This 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781032713823

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