Applied Statistics and Data Science: Proceedings of Statistics 2021 Canada, Selected Contributions

This proceedings volume presents top contributions in modern statistical methods from Statistics 2021 Canada, covering Bayesian statistics, computational statistics, data science, semi-parametric regression, and stochastic methods. It is a valuable resource for graduate students, researchers, and practitioners.

Format: Paperback / softback
Length: 159 pages
Publication date: 09 December 2022
Publisher: Springer Nature Switzerland AG

This proceedings volume presents a selection of outstanding contributions in modern statistical methods from the 6th Annual Canadian Conference in Applied Statistics (Statistics 2021 Canada), which took place virtually from July 15 to 18, 2021. The conference brought together established and emerging scholars from various fields, showcasing cutting-edge and contemporary innovative techniques in statistics and data science. The contributions cover a wide range of topics, including Bayesian statistics, computational statistics, data science, semi-parametric regression, and stochastic methods applied to biology, crop science, ecology, and engineering.

The volume serves as a valuable resource for graduate students, researchers, and practitioners seeking to expand their knowledge and expertise in applied statistical and data science methods. It offers a comprehensive overview of the latest developments and applications in these fields, providing insights into the latest research trends and methodologies.

The papers in this proceedings volume were carefully reviewed and selected by a panel of experts in the field, ensuring that they represent the state-of-the-art in statistical research. The contributions are written in a clear and concise manner, making them accessible to a broad audience, including those with limited statistical background.

In conclusion, this proceedings volume showcases the remarkable achievements and advancements in modern statistical methods by researchers from across Canada and around the world. It provides a valuable platform for disseminating knowledge and fostering collaboration in the field. We hope that it will inspire further research and development in statistical science and its applications to address real-world problems.

Introduction:
The 6th Annual Canadian Conference in Applied Statistics (Statistics 2021 Canada) was a virtual event held from July 15 to 18, 2021, bringing together scholars from various fields to discuss and showcase cutting-edge statistical methods and applications. This proceedings volume features a selection of top contributions in modern statistical methods, reflecting the diverse expertise and innovative approaches present at the conference.

Contributions:
The volume includes papers contributed by established and emerging scholars from Canada and around the world. The contributions cover a wide range of topics, including Bayesian statistics, computational statistics, data science, semi-parametric regression, and stochastic methods applied to biology, crop science, ecology, and engineering.

Bayesian statistics is a powerful tool for statistical inference, particularly in the context of complex models and data with high dimensionality. The papers in this volume explore various Bayesian approaches, such as Markov chain Monte Carlo (MCMC) methods, hierarchical Bayesian models, and Bayesian networks, for analyzing data and making predictions. Computational statistics is an essential component of modern statistical analysis, and the papers in this volume discuss efficient algorithms and software for solving statistical problems, including optimization, simulation, and machine learning.

Data science is a rapidly growing field that combines statistics, computer science, and domain knowledge to analyze and interpret large datasets. The papers in this volume discuss data visualization, machine learning algorithms, and statistical modeling techniques for understanding complex phenomena and making informed decisions. Semi-parametric regression is a flexible approach that combines the advantages of parametric and non-parametric models, allowing for the analysis of data with non-normal distributions and missing data. The papers in this volume explore semi-parametric regression methods for various applications, including disease modeling, financial analysis, and environmental studies.

Stochastic methods are widely used in biology, crop science, ecology, and engineering to model and analyze complex systems characterized by randomness. The papers in this volume discuss stochastic models for population dynamics, disease transmission, and resource allocation, as well as their applications in risk assessment, decision-making, and optimization.

Conclusion:
The proceedings volume presented here showcases the remarkable contributions made by researchers in modern statistical methods. The papers cover a wide range of topics and applications, reflecting the growing importance of statistical research and its applications in various fields. The volume will be a valuable resource for graduate students, researchers, and practitioners seeking to expand their knowledge and expertise in applied statistical and data science methods. We hope that this proceedings volume will inspire further research and collaboration in statistical science and its applications to address real-world problems.

Weight: 279g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030861353
Edition number: 1st ed. 2021