Illustrating Statistical Procedures Finding Meaning In Quantitative Data

This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis.

This new edition updates a text that provides a set of descriptions for various statistical procedures as they are applied in the conduct of business, behavioral and social science research.

This handbook provides an in-depth exploration of the entire journey of postgraduate research in the social and behavioural sciences, from enrolment to its culmination in the form of a thesis, dissertation or portfolio, and beyond. It is written in an accessible and example-rich style, offering practical and concrete advice in virtually all areas. It also includes references to additional resources and websites, and each chapter features key recommendations for improving the postgraduate research experience. The book addresses not only research-related aspects (e.g. supervisors; selecting your guiding assumptions; contextualising, framing and configuring research; reviewing literature; sampling; writing proposals; ethics and academic integrity; selecting a data gathering strategy; surviving your thesis/dissertation/portfolio examination; and publishing), but also questions concerning how to integrate, manage, and balance the research journey in the context of the postgraduate student’s broader life-world (e.g. skill development and supervisor relations; effective time and project management; a healthy work–life balance; maintaining motivation; and dealing with criticism). The book adopts an explicitly pluralist perspective on postgraduate research, moving beyond mixed methods thinking, and offers concrete examples from postgraduate students’ real-world experiences.

Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.

This book covers various aspects of remote sensing and geographic information systems, from the perspective of earth and environmental sciences. The theme of applications of remote sensing and geographic information systems for the purposes of sustainable development highlights the innovative usage of space imaged spectral data in soil characterization. This book merges the selected contributions to the First International Conference of Remote Sensing and Space Sciences Applications (Egypt 2022) aiming to promote the latest findings on the development of Space Technologies and Applications.

The aim of this text is to provide a set of descriptions for various statistical procedures as they are applied in the conduct of business, behavioral and social science research.

Artificial Intelligence (AI) is a rapidly developing field of computer science which now plays an increasingly important role in many disciplines. A catalyst for significant change, research into AI is of particular importance in fields such as medicine and education, and as such has become an area to watch for many people worldwide. This book presents the proceedings of AIMEE 2023, the 7th International Conference on Artificial Intelligence, Medical Engineering and Education, held on 9 and 10 November 2023 in Guangzhou, China. The conference brought together top international researchers from around the world to exchange research results and address open issues in AI, medical engineering and education. A total of 238 submissions were received for AIMEE 2023, of which 89 papers were selected for presentation and publication after a rigorous international peer review process. The book is divided into 3 sections, covering artificial intelligence and scientific methodology; systems engineering and analysis: concepts, methods, and applications; and education reform and innovation. Presenting papers which explore and discuss many novel concepts and methodologies contributing to the rapid evolution of artificial intelligence and its applications, the book will be of interest to all those working in the relevant fields.