Advance Research Trends in Statistics and Data Science

The present book of Statistics and Data Science provides an accessible introduction to statistics for data scientists by uniquely combining hands-on exercises with mathematical theory. We include many practical applications of statistical methods and dataanalysis from various fields. The chapters are grouped into basic techniques and applications. The present volume is based on the contributions made by various authors on different important topic of “Advance Research Trends in Statistics and Data Science” and introduces the subject along the following topics:Analysis of Sampling on Successive Occasions;Biostatistics: Types of data and Data Presentation; Bayesian Approach for the scale parameter of Positive exponential family of distributions; Software Reliability-A Brief Review; An Overview of Artificial Neural Networks (ANNs): Concepts and Applications; Machine Learning Applications in Cancer Prediction and Prognosis; Maternal Health Situation in Bihar and Assam: A Comparative Analysis of State Fact Sheets of National Family Health Survey (NFHS)-4 and (NFHS)-5; Application of Cloud Computing in Libraries; Classical and Bayesian Estimation of the Process Capability Index Cpy Based on Lomax Distributed Quality Characteristic; Bayesian Inferences in Generalized Lindley Shared Frailty Model with Left Censored Bivariate Data; Biostatistics; and Applications and Demonstration of Bootstrap and Other Resampling Technique