Georgios Halkias – författare

The earliest examples of Buddhist studies originating in the Western world tended to frame Buddhism as a religion similar to Abrahamic monotheisms. This involved, among other things, an emphasis on philological, doctrinal, and textual studies, as well as an assumption that the Buddha compares directly to the messianic figures central to other traditions. Starting in the late twentieth century, Buddhist studies scholars have been creatively moving outside of this rubric, and indeed outside of the familiar boundaries of the academy. This movement has allowed them to examine subjects, perspectives, and methodologies not previously engaged by the mainstream of Buddhist studies. Such a wider approach fosters greater awareness of external versus internal critiques of the religion, inclusion of new disciplines and previously marginalized voices, and an appreciation of the decentralized nature of Buddhism and the varied personal experiences of lived practice. As a result, Buddhist studies has attracted a growing audience within the humanities and has been at the forefront of the discourse on cultural exchange, globalization, colonialism and postcolonialism, and the ongoing changes in the religious landscape. Reflecting these innovations, The Oxford Encyclopedia of Buddhism is a first-of-its-kind reference project: a systematic effort to identify and analyze the ways in which Buddhist studies continues to develop, the new sub-fields of inquiry, and the evolving relationships between the related disciplines. Consisting of 138 in-depth articles, the Encyclopedia covers several major thematic areas, including historical and historiographical studies, historical figures, buddhas and deities, regional studies, global and diasporic Buddhism, art and architecture, contemporary social and academic issues, rituals, philosophical and doctrinal studies, textual and philological studies, and the most influential educational institutions. Moreover, the Encyclopedia frames Buddhist studies as a field rather than as a discipline, meaning that it covers a rich variety of intellectual projects. This approach balances independent specialized studies with interconnected and interdisciplinary studies, inviting research that is both sharper and more nuanced. It is this perspective, gazing toward the future of the field, that marks the volume as an essential work of contemporary scholarship and an organically evolving encyclopedia for study and research.

Taking the Fear Out of Data Analysis provides readers with the necessary knowledge and skills to understand, perform, and interpret quantitative data analysis effectively. Acknowledging that people often dislike statistics and quantitative methods, this book illustrates that statistical reasoning can be a fun and intuitive part of our lives.Key Features:Split into three sections covering how to understand data, preparing data for analysis and carrying out the analysisBlends theory with practical examples in a logical and straightforward manner to guide readers in making sense of statistical inferenceOffers universal knowledge that can be applied to a variety of software applications with limited technical complexity to aid the learning processShort and concise chapters focusing on the essence of the topics covered, such as analytical techniques that are typically used in behavioral and social science researchSignificantly revised and updated, this textbook is an essential text for both undergraduate and postgraduate students in fields such as information systems, international business and marketing. It will also be beneficial for practitioners involved in data science, data analytics, and market research.

Taking the Fear Out of Data Analysis provides readers with the necessary knowledge and skills to understand, perform, and interpret quantitative data analysis effectively. Acknowledging that people often dislike statistics and quantitative methods, this book illustrates that statistical reasoning can be a fun and intuitive part of our lives.

Key Features:

Split into three sections covering how to understand data, preparing data for analysis and carrying out the analysisBlends theory with practical examples in a logical and straightforward manner to guide readers in making sense of statistical inferenceOffers universal knowledge that can be applied to a variety of software applications with limited technical complexity to aid the learning processShort and concise chapters focusing on the essence of the topics covered, such as analytical techniques that are typically used in behavioral and social science research

Significantly revised and updated, this textbook is an essential text for both undergraduate and postgraduate students in fields such as information systems, international business and marketing. It will also be beneficial for practitioners involved in data science, data analytics, and market research.