Advanced Statistical Methods In Data Science
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Advanced Statistical Methods In Data Science
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Author : Ding-Geng Chen
language : en
Publisher: Springer
Release Date : 2016-11-30
Advanced Statistical Methods In Data Science written by Ding-Geng Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-30 with Mathematics categories.
This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.
Advanced Statistical Methods In Life Science
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Author : Basavarajaiah D.M
language : en
Publisher: CRC Press
Release Date : 2025-07-25
Advanced Statistical Methods In Life Science written by Basavarajaiah D.M and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-25 with Mathematics categories.
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.
Understanding Advanced Statistical Methods
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Author : Peter Westfall
language : en
Publisher: CRC Press
Release Date : 2013-04-09
Understanding Advanced Statistical Methods written by Peter Westfall and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-09 with Mathematics categories.
Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian me
Advanced Statistical Analytics For Health Data Science With Sas And R
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Author : Ding-Geng (Din) Chen
language : en
Publisher: CRC Press
Release Date : 2025-09-16
Advanced Statistical Analytics For Health Data Science With Sas And R written by Ding-Geng (Din) Chen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-16 with Mathematics categories.
In recent years, there has been a growing emphasis on making statistical methods and analytics accessible to health data science researchers and students. Following the first book on "Statistical Analytics for Health Data Science with SAS and R" (2023, www.routledge.com/9781032325620), this book serves as a comprehensive reference for health data scientists, bridging fundamental statistical principles with advanced analytical techniques. By providing clear explanations of statistical theory and its application to real- world health data, we aim to equip researchers with the necessary tools to navigate the evolving landscape of health data science. Designed for advanced-level data scientists, this book covers a wide range of statistical methodologies, including models for longitudinal data with time-dependent covariates, multi-membership mixed-effects models, statistical modeling of survival data, Bayesian statistics, joint modeling of longitudinal and survival data, nonlinear regression, statistical meta-analysis, spatial statistics, structural equation modeling, latent growth curve modeling, causal inference, and propensity score analysis. A key feature of this book is its emphasis on real-world applications. We integrate publicly available health datasets and provide case studies from a variety of health applications. These practical examples demonstrate how statistical methods can be applied to solve critical problems in health science. To support hands-on learning, we offer implementation guidance using SAS and R, ensuring that readers can replicate analyses and apply statistical techniques to their own research. Step-by-step computational examples facilitate reproducibility and deeper exploration of statistical models. By combining theoretical foundations with practical applications, this book empowers health data scientists to develop robust statistical solutions for complex health challenges. Whether working in academia, industry, or public health, readers will gain the expertise to advance data-driven decision-making and contribute to evidence-based health research.
Advanced Statistical Methods For The Analysis Of Large Data Sets
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Author : Agostino Di Ciaccio
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-03-05
Advanced Statistical Methods For The Analysis Of Large Data Sets written by Agostino Di Ciaccio and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-05 with Mathematics categories.
The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”
Advanced Statistical Methods
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Author : Sahana Prasad
language : en
Publisher: Springer Nature
Release Date : 2024-05-11
Advanced Statistical Methods written by Sahana Prasad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-11 with Mathematics categories.
This is the second book of the two volumes covering the advanced statistical methods and analysis. Significant topics include advanced concepts in regression, index numbers, time series, and vital statistics. The book includes useful examples and exercises as well as relevant case studies for proper implementation of the discussed tools. This book will be a valuable text for advanced undergraduate students of statistics, management, economics, and psychology, wanting to gain advanced understanding of statistics and the usage of its various concepts.
Advanced Computing
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Author : Deepak Garg
language : en
Publisher: Springer Nature
Release Date : 2022-02-07
Advanced Computing written by Deepak Garg and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-07 with Computers categories.
This volume constitutes reviewed and selected papers from the 11th International Advanced Computing Conference, IACC 2021, held in December 2021. The 47 full papers and 4 short papers presented in the volume were thorougly reviewed and selected from 246 submissions. The papers are organized in the following topical sections: application of artificial intelligence and machine learning in healthcare; application of AI for emotion and behaviour prediction; problem solving using reinforcement learning and analysis of data; advance uses of RNN and regression techniques; special intervention of AI.
Statistical Methods Using Spss
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Author : Gabriel Otieno Okello
language : en
Publisher: CRC Press
Release Date : 2024-09-18
Statistical Methods Using Spss written by Gabriel Otieno Okello and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-18 with Mathematics categories.
Statistical Methods Using SPSS provides a practical approach for better understanding of the advanced statistical concepts that are applied in business, economics, epidemiology, public health, agriculture and other areas of data analytics. Advanced statistical methods or advanced statistical techniques for analyzing data arise because of the complex nature of data sets that cannot be analyzed using the basic or the usual and common analytical techniques. This book describes more advanced statistical methods, offering a modern approach by introducing the advanced statistical concepts, before showing the application of these concepts in real-world examples with the application of SPSS statistical software. This book is useful in explaining advanced statistical analysis techniques to postgraduate students, doctoral students and researchers. It is also a useful reference for students and researchers who require further guidance in advanced data analysis and is designed for those with basic statistical knowledge. Exercises are also included at the end of each chapter to aid in the understanding of the statistical analysis techniques explained in the book. Key features: there are many topics on advanced statistical techniques, a provision of theoretical statistical concepts, there is a step-by-step guide for the different statistical analysis techniques being done using SPSS, there are variety of data set examples to help explain the different statistical concepts, and there is a practical applications of the statistical concepts in SPSS.
New Advances In Statistics And Data Science
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Author : Ding-Geng Chen
language : en
Publisher: Springer
Release Date : 2018-01-17
New Advances In Statistics And Data Science written by Ding-Geng Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-17 with Mathematics categories.
This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.
Advanced Methods In Statistics Data Science And Related Applications
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Author : Matilde Bini
language : en
Publisher: Springer Nature
Release Date : 2024-10-16
Advanced Methods In Statistics Data Science And Related Applications written by Matilde Bini and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-16 with Computers categories.
This book contains a selection of the improved contributions submitted by participants at the conference of the Italian Statistical Society - SIS 2022 held in Caserta 22-24 June 2022. The scientific community of Italian statistics, which gathers around the SIS, is paying particular attention to the development of statistical techniques increasingly oriented toward the processing of large data, mainly, of complex data. The main goal is to provide the analysis of the data and the interpretability of the obtained results, with a view to decision support and the reliability of the data outcomes. The aim of this volume is to show some of the most relevant contributions of statistical and data analysis methods in preserving the quality of the information to be processed, especially when it comes from different, often non-official sources; as well as in the extraction of knowledge from complex data (textual, network, unstructured and multivalue) and in the explicability of results. Data Science today represents a broad domain of knowledge development from data, where statistical and data analysis methods can make an important contribution in the different domains where data management and processing are required. This volume is addressed to researchers but also to Ph.D. and MSc students in the field of Statistics and Data Science to acquaint them with some of the most recent developments towards which statistical research is orienting, in prevalence in Italy.