
Advanced Statistical Methods in Life Science
- 320 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Advanced Statistical Methods in Life Science
About this book
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.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Dedication
- Table of Contents
- Preface
- Authors
- 1 Diagrammatic Representation of Life Science Research: A Comprehensive Overview
- 2 A Comprehensive Guide to Descriptive Statistics on Measures of Central Tendency and Dispersion
- 3 Correlation and Regression Analysis: A Beginnerʼs Guide
- 4 Exploring the Applications of the Theory of Probability
- 5 Recent Probability Distribution and Statistical Methods in Life Science Research
- 6 An Expertʼs Guide to Using Statistical Hypothesis for Life Science
- 7 Exploring Statistical Performance: Strategies to Study Molecular Genetics
- 8 Unleash the Potential of Proteomics Data with Statistical Application in Biochemistry
- 9 Statistical Tools for Clinical Trials in Medical Research
- 10 An Introduction to Sampling Techniques and Sample Size Determination in Biological Science Research
- 11 A Comprehensive Overview of Machine Learning and Artificial Neural Network Modeling
- 12 Applying Meta-Analysis in the New Trend of Scientific Scenarios
- 13 Uncovering the Top N Nonparametric Tests in Life Science
- 14 Statistical Ethics and Future Line of Research Work
- Index