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Full Description
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.
Contents
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 Beginner's Guide 4. Exploring the Applications of the Theory of Probability 5. Recent Probability Distribution and Statistical Methods in Life Science Research 6. An Expert's 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 Modelling 12. Applying Meta Analysis in the new trend of Scientific Scenario 13. Uncovering the Top N Nonparametric Tests in Life Science 14. Statistical Ethics and Future Line of Research Work
