A decade on from its birth, emotional intelligence is attracting more attention than ever before. Why? Because of its proven connection to performance. Tomorrow's leaders will have to be facilitators who work collaboratively to help others develop their potential, and this will require emotionally intelligent skills and attitudes. Against this landscape, Applied EI provides the tools and advice needed to develop and manage a relationship with yourself and create positive relationships with others - the twin cornerstones of emotional intelligence. We're all capable of acting with emotional intelligence. Most of us don't, because internal interferences - misguided beliefs and attitudes learnt in childhood - get in the way. Countering this, Applied EI attaches unique importance to the role of attitudes in developing and applying emotional intelligence. Tim Sparrow and Amanda Knight stress that EI isn't a synonym for personality; it's about managing personality. That's why knowing how to put EI into practice is essential. And that's why reducing EI to a single number or score misses the point, and serves only to give us another measure by which to judge ourselves and others. Anyone interested in performance improvement today needs to be interested in emotional intelligence. Applied EI shows how our attitudes underpin our EI, explores how to develop emotionally intelligence attitudes, and lays out tactics for applying them in practice. It discusses what is needed at individual, team and leadership development levels, and considers what it means to be an EI practitioner. Its practical approach and unique perspective make it a must-read for anyone involved in the field of personal development.

Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor. The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields. While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution. The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration.