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Probability and statistics

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Nowadays, the information transfer speed (on the web, but not only) requires the predisposition of ever more adequate analysis tools for working with data and increasingly faster algorithms, in order to allow the so-called decision maker to make decision based on information which can become obsolete very quickly with time. In the current situation, analysing this information in order to simulate complex decision-making scenarios could prove fundamental to secure an advantage over competitors. This text introduces the true art of Statistical Computing. In other words, it illustrates how computer programming skills in the development of algorithms can be used within Statistics for the virtual simulation and replication of realities and experiments of varying complexity. In order to do so, it uses the excellent development environment "R".

Probability measures. --- Probability and statistics.

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Rarely, but just often enough to rebuild hope, something happens to confound my pessimism about the recent unprecedented happenings in the world. This book is the most recent instance, and I think that all its readers will join me in rejoicing at the good it seeks to do. It is an example of the kind of international comity and collaboration that we could and should undertake to solve various societal problems. This book is a beautiful example of the power of the possible. [It] provides a blueprint for how the LISA 2020 model can be replicated in other fields. Civil engineers, or accountants, or nurses, or any other profession could follow this outline to share expertise and build capacity and promote progress in other countries. It also contains some tutorials for statistical literacy across several fields. The details would change, of course, but ideas are durable, and the generalizations seem pretty straightforward. This book shows every other profession where and how to stand in order to move the world. I urge every researcher to get a copy!"--David Banks from the Foreword Promoting Statistical Practice and Collaboration in Developing Countries provides new insights into the current issues and opportunities in international statistics education, statistical consulting, and collaboration, particularly in developing countries around the world. The book addresses the topics discussed in individual chapters from the perspectives of the historical context, the present state, and future directions of statistical training and practice, so that readers may fully understand the challenges and opportunities in the field of statistics and data science, especially in developing countries. Features Reference point on statistical practice in developing countries for researchers, scholars, students, and practitioners Comprehensive source of state-of-the-art knowledge on creating statistical collaboration laboratories within the field of data science and statistics Collection of innovative statistical teaching and learning techniques in developing countries Each chapter consists of independent case study contributions on a particular theme that are developed with a common structure and format. The common goal across the chapters is to enhance the exchange of diverse educational and action-oriented information among our intended audiences, which include practitioners, researchers, students, and statistics educators in developing countries.

Statistics --- Developing countries. --- Study and teaching. --- Probability and statistics

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Probabilities --- Mathematical statistics --- Statistics --- Probabilités --- Statistique mathématique --- Statistique --- History --- Histoire --- Mathemathics --- Probability and Statistics

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681.3*G3 --- 519.217 --- Probability and statistics: probabilistic algorithms (including Monte Carlo)random number generation statistical computing statistical software (Mathematics of computing) --- Markov processes --- 519.217 Markov processes --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo)random number generation statistical computing statistical software (Mathematics of computing) --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- Stochastic processes. --- Stochastic processes --- Processus stochastiques