John Chen – författare

Multivariate Bonferroni-Type Inequalities: Theory and Applications presents a systematic account of research discoveries on multivariate Bonferroni-type inequalities published in the past decade. The emergence of new bounding approaches pushes the conventional definitions of optimal inequalities and demands new insights into linear and Fréchet optimality. The book explores these advances in bounding techniques with corresponding innovative applications. It presents the method of linear programming for multivariate bounds, multivariate hybrid bounds, sub-Markovian bounds, and bounds using Hamilton circuits. The first half of the book describes basic concepts and methods in probability inequalities. The author introduces the classification of univariate and multivariate bounds with optimality, discusses multivariate bounds using indicator functions, and explores linear programming for bivariate upper and lower bounds. The second half addresses bounding results and applications of multivariate Bonferroni-type inequalities. The book shows how to construct new multiple testing procedures with probability upper bounds and goes beyond bivariate upper bounds by considering vectorized upper and hybrid bounds. It presents an optimization algorithm for bivariate and multivariate lower bounds and covers vectorized high-dimensional lower bounds with refinements, such as Hamilton-type circuits and sub-Markovian events. The book concludes with applications of probability inequalities in molecular cancer therapy, big data analysis, and more.

Use technology to increase loyalty and productivity in your employees 50 Digital Team-Building Games offers fun, energizing meeting openers, team activities, and group adventures for business teams, using Twitter, GPS, Facebook, smartphones, and other technology. The games can be played in-person or virtually, and range from 5-minute ice-breakers to an epic four-hour GPS-based adventure. Designed to be lead by managers, facilitators, presenters, and speakers, the activities help teams and groups get comfortable with technology, get to know each other better, build trust, improve communication, and more. No need to be a "techie" to lead these games—they're simple and well-scripted.Author John Chen is the CEO of Geoteaming, a company that uses technology and adventure to teach teams how to collaborate. How to lead a simple, fast, fun team building activity with easy-to-follow instructionsHow to create successful "virtual" team building that requires NO travel and little to no additional expensesHow to engage standoffish engineers, "hard to reach" technical teams, or Gen X/Y teammates with technology they enjoy usingSuccessful technology-based team building can build buzz for your company, build critically important relationships and communication internally, and keep your team talking about it for weeks afterward!

Build a cohesive and high-performing virtual team with this fantastic resource full of actionable advice and practical tipsEngaging Virtual Meetings: Openers, Games, and Activities for Communication, Morale, and Trust offers concrete strategies and practical tips for bringing teams together across the digital divide. While many struggle to build teams in a virtual environment, accomplished author John Chen has found ways to create team cohesion, promote engagement, and increase virtual participation. In Engaging Virtual Meetings, he shares these methods with you, and also: Describes virtual tools for promoting effective teamwork, like the Participant MapTeaches you to optimize your teleconference setup for ideal audio and videoIllustrates ways to apply these methods in any virtual environment, including Zoom, Microsoft Teams, and moreExplores how to debrief your participants to improve your methods over timePerfect for anyone working in or with the increasingly prevalent virtual environment, Engaging Virtual Meetings is a great addition to the bookshelves of anyone interested in how to create and build engagement in team settings of all kinds.

Multivariate Bonferroni-Type Inequalities: Theory and Applications presents a systematic account of research discoveries on multivariate Bonferroni-type inequalities published in the past decade. The emergence of new bounding approaches pushes the conventional definitions of optimal inequalities and demands new insights into linear and Fréchet optimality. The book explores these advances in bounding techniques with corresponding innovative applications. It presents the method of linear programming for multivariate bounds, multivariate hybrid bounds, sub-Markovian bounds, and bounds using Hamilton circuits. The first half of the book describes basic concepts and methods in probability inequalities. The author introduces the classification of univariate and multivariate bounds with optimality, discusses multivariate bounds using indicator functions, and explores linear programming for bivariate upper and lower bounds. The second half addresses bounding results and applications of multivariate Bonferroni-type inequalities. The book shows how to construct new multiple testing procedures with probability upper bounds and goes beyond bivariate upper bounds by considering vectorized upper and hybrid bounds. It presents an optimization algorithm for bivariate and multivariate lower bounds and covers vectorized high-dimensional lower bounds with refinements, such as Hamilton-type circuits and sub-Markovian events. The book concludes with applications of probability inequalities in molecular cancer therapy, big data analysis, and more.

Wackerly/Chen/Loy’s “Mathematical Statistics with Applications” 8th Edition, with WebAssign, builds a solid foundation in statistical theory while conveying its relevance in solving practical problems in the real world. You'll discover the nature of statistics and understand its essential role in scientific research. The focused approach emphasizes the connectivity of key concepts with statistical inference being the primary theme. The new edition offers enhanced insights and cutting-edge knowledge on theory and applications of statistics today, including new methodologies in data science, statistical learning and biostatistics.