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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 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 offers extensive and valuable advice for researchers starting with pharmaceutical studies and doctoral dissertation writing. The contributors provide precise, detailed instructions covering every phase of the research process, from choosing a topic to sharing findings, because they know the intricacies and difficulties that come with it. Essential topics covered in the book include writing a professional thesis, conducting literature reviews, planning experimental methods, and guaranteeing ethical human and animal research procedures. The book promises to provide researchers with the information and abilities required to succeed academically and professionally in the pharmaceutical sciences through helpful guidance, software tool recommendations, and communication techniques. Summary of the book This thorough manual is vital for researchers since it covers every pharmaceutical research and thesis composing stage. It starts with methods for choosing a study topic that is both possible and relevant. Key areas of exploration are identified by utilizing resources such as YouTube, LinkedIn, published papers, and reviews. The book leads users through creating a synopsis and offers precise, step-by-step guidance on successfully communicating your research. Essential phases of carrying out an exhaustive literature study are addressed, guaranteeing that you establish a firm basis by examining current material and pinpointing deficiencies. After that, the book moves on to planning and carrying out experiments, emphasising the significance of physicochemical characterisation, drug and excipient compatibility, and formulation development. It emphasises using QbD principles to optimise and evaluate various dosage forms alongside in vitro studies. Practical aspects of conducting animal and human studies ethically and effectively are addressed, followed by guidance on writing a compelling thesis. The book underscores the significance of professional writing in achieving a doctoral certificate and provides tips for image preparation, crucial for thesis writing. It also discusses various statistical, drug design, and research writing software tools. Finally, the guide prepares you for defending your thesis and offers advice on publishing and disseminating your findings to ensure your research reaches a broader audience. With its step-by-step approach and accessible language, this book is an invaluable companion for researchers embarking on pharmaceutical research and thesis writing across diverse fields.
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.
As e-commerce continues to increase in usage and popularity, safeguarding consumers private data becomes critical. Strategic innovations in artificial intelligence and machine learning revolutionize data security by offering advanced tools for threat detection and mitigation. Integrating AI and machine learning into their security solutions will allow businesses to build customer trust and maintain a competitive edge throughout the growing digital landscapes. A thorough examination of cutting-edge innovations in e-commerce data security may ensure security measures keep up with current technological advancements in the industry. Strategic Innovations of AI and ML for E-Commerce Data Security explores practical applications in data security, algorithms, and modelling. It examines solutions for securing e-commerce data, utilizing AI and machine learning for modelling techniques, and navigating complex algorithms. This book covers topics such as data science, threat detection, and cybersecurity, and is a useful resource for computer engineers, data scientists, business owners, academicians, scientists, and researchers.
The field of biology and technology is constantly changing and growing. However, the abundance and intricacy of biological data present significant challenges for researchers, educators, and students. Deciphering this vast sea of information to extract meaningful insights can be difficult. Traditional approaches often fail to provide comprehensive solutions to these intricate problems, leaving many struggling to navigate the complexities of bioinformatics. Effective Techniques for Bioinformatic Exploration brings new clarity to the world of bioinformatics, offering a comprehensive solution to the challenges scholars face. Through its meticulously crafted chapters, this book provides a structured approach to understanding and applying bioinformatics principles. Bridging the gap between theory and practice equips readers with the tools needed to tackle complex biological problems effectively. Whether delving into genomics, proteomics, or machine learning models, this book offers a roadmap for success. This book empowers readers to overcome challenges and make meaningful contributions to the field by embracing the scientific method and showcasing the practical application of bioinformatics techniques.
This is a textbook for introductory courses in quantitative research methods across the social sciences. It offers a detailed explanation of introductory statistical techniques and presents an overview of the contexts in which they should be applied.