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This definitive edition, the first since 1974, presents all the poetry of Samuel Johnson (1709–1784), including his play, Irene, with detailed, wide-ranging commentary. It has been expertly edited with attention to the extant manuscripts and all relevant printings.The volume includes the entirety of Johnson's verse in all its generic diversity: including satire, ode, elegy, verse drama, and verse prayer. The poems are presented in their original spelling and punctuation with extensive commentary on their literary background—biblical, classical, and modern—as well as careful explanation of unusual words, allusions to historical figures, and references to contemporary events that appear in the poems. Proceeding chronologically, this edition also situates Johnson's verse in the context of his life from his early days in Lichfield to his career as an author in London. Unlike all earlier editions, the present offering provides full translations of all the Latin and Greek poems on which Johnson based so much of his English verse. Correspondingly, it provides the English poems which some of his Latin verse translates. Neither in the presentation of the verse nor in the commentary does this edition assume a command of foreign languages: it aims to be useful for all students of Samuel Johnson's poetry.

This tutorial teaches you how to use the statistical programming language R to develop a business case simulation and analysis. It presents a methodology for conducting business case analysis that minimizes decision delay by focusing stakeholders on what matters most and suggests pathways for minimizing the risk in strategic and capital allocation decisions. Business case analysis, often conducted in spreadsheets, exposes decision makers to additional risks that arise just from the use of the spreadsheet environment. R has become one of the most widely used tools for reproducible quantitative analysis, and analysts fluent in this language are in high demand. The R language, traditionally used for statistical analysis, provides a more explicit, flexible, and extensible environment than spreadsheets for conducting business case analysis. The main tutorial follows the case in which a chemical manufacturing company considers constructing a chemical reactor and production facility to bring a new compound to market. There are numerous uncertainties and risks involved, including the possibility that a competitor brings a similar product online. The company must determine the value of making the decision to move forward and where they might prioritize their attention to make a more informed and robust decision. While the example used is a chemical company, the analysis structure it presents can be applied to just about any business decision, from IT projects to new product development to commercial real estate. The supporting tutorials include the perspective of the founder of a professional service firm who wants to grow his business and a member of a strategic planning group in a biomedical device company who wants to know how much to budget in order to refine the quality of information about critical uncertainties that might affect the value of a chosen product development pathway. What You'll LearnSet upa business case abstraction in an influence diagram to communicate the essence of the problem to other stakeholdersModel the inherent uncertainties in the problem with Monte Carlo simulation using the R languageCommunicate the results graphicallyDraw appropriate insights from the resultsDevelop creative decision strategies for thorough opportunity cost analysisCalculate the value of information on critical uncertainties between competing decision strategies to set the budget for deeper data analysisConstruct appropriate information to satisfy the parameters for the Monte Carlo simulation when little or no empirical data are available Who This Book Is For Financial analysts, data practitioners, and risk/business professionals; also appropriate for graduate level finance, business, or data science students

The first International Conference on the Biology of Deer Production was held at Dunedin, New Zealand in 1983. That meeting provided, for the first time, a forum for those with interests in either wild deer management or farmed deer production to come together. Scientists, wild deer managers, domestic deer farmers, veterinarians, venison and antler product producers, and others were able to discuss common problems and to share their knowledge and experience. The relationships formed at that meeting, and the information amassed in the resulting Proceedings, sparked new endeavors in cervid research, management, and production. A great deal has taken place in the world of deer biology since 1983. Wild deer populations, although ever increasing in many areas of the world, face new hazards of habitat loss, environmental contamination, and overexploitation. Some species are closer to extinction than ever. Game managers often face political as well as biological challenges. Many more deer are now on farms, leading to greater concerns about disease control and increased needs for husbandry information. Researchers have accumulated considerable new in­ formation, some of it in areas such as biochemical genetics, not discussed in 1983.