Advanced Statistical Methods In Life Science
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Advanced Statistical Methods in Life Science
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.
Design of Experiments and Advanced Statistical Techniques in Clinical Research
Author: Basavarajaiah D. M.
language: en
Publisher: Springer Nature
Release Date: 2020-11-05
Recent Statistical techniques are one of the basal evidence for clinical research, a pivotal in handling new clinical research and in evaluating and applying prior research. This book explores various choices of statistical tools and mechanisms, analyses of the associations among different clinical attributes. It uses advanced statistical methods to describe real clinical data sets, when the clinical processes being examined are still in the process. This book also discusses distinct methods for building predictive and probability distribution models in clinical situations and ways to assess the stability of these models and other quantitative conclusions drawn by realistic experimental data sets. Design of experiments and recent posthoc tests have been used in comparing treatment effects and precision of the experimentation. This book also facilitates clinicians towards understanding statistics and enabling them to follow and evaluate the real empirical studies (formulation of randomized control trial) that pledge insight evidence base for clinical practices. This book will be a useful resource for clinicians, postgraduates scholars in medicines, clinical research beginners and academicians to nurture high-level statistical tools with extensive scope.
Research Methodology –Biostatistics & Life Science
Author: Prasanth.C. B
language: en
Publisher: Academic Guru Publishing House
Release Date: 2024-11-26
"Research Methodology - Biostatistics & Life Science" offers a comprehensive examination of the statistical principles and research methodologies that are vital for conducting research in the life sciences. This book is organized into logical sections that encompass the entire research process, from the initial phases of problem identification to the final steps of data analysis and interpretation. The book addresses critical subjects, including the utilization of sophisticated instruments such as SPSS and SAS for data analysis, hypothesis testing, descriptive and inferential statistics, and experimental design. It also underscores the significance of ethics in research, guaranteeing that readers are cognizant of the ethical implications of their work in biological and health- related fields. The book also delves into the function of biostatistics in life science research, emphasizing its applications in the analysis of biological data, clinical trials, epidemiological studies, and public health research. The book simplifies intricate statistical concepts for readers from a variety of academic and professional backgrounds by providing practical examples, case studies, and real- world applications. It also addresses future trends in life science research, interdisciplinary approaches, and emergent research techniques, providing readers with the necessary knowledge to excel in this constantly changing field.