Statistics and Computing/Statistics Programs.
概観
著作: | 86 作品に 86 出版物中に 86 言語 |
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タイトル
Econometric analysis of carbon markets[electronic resource] :the European Union emissions trading scheme and the clean development mechanism /
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Excel 2010 for educational and psychological statistics[electronic resource] :a guide to solving practical problems /
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Business statistics for competitive advantage with Excel 2010[electronic resource] :basics, model building, and cases /
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Advanced statistical methods for the analysis of large data-sets[electronic resource] /
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Excel 2007 for social science statistics[electronic resource] :a guide to solving practical problems /
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Excel 2010 for social science statistics[electronic resource] :a guide to solving practical problems /
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COMPSTAT 2008[electronic resource] :proceedings in computational statistics : 18th Symposium held in Porto, Portugal, 2008 /
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Contingency table analysis[electronic resource] :methods and implementation using R /
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Translational recurrences[electronic resource] :from mathematical theory to real-world applications /
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The significance test controversy revisited[electronic resource] :the fiducial Bayesian alternative /
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Analysis and modeling of complex data in behavioral and social sciences[electronic resource] /
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Recent advances in natural computing[electronic resource] :selected results from the IWNC 7 symposium /
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Excel 2013 for business statistics[electronic resource] :a guide to solving practical business problems /
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Excel 2013 for biological and life sciences statistics[electronic resource] :a guide to solving practical problems /
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New ecoinformatics tools in environmental science[electronic resource] :applications and decision-making /
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Gravitational wave detection and data analysis for pulsar timing arrays[electronic resource] /
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Software reliability modeling[electronic resource] :fundamentals and applications /
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High-performance in-memory genome data analysis[electronic resource] :how in-memory database technology accelerates personalized medicine /
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Introduction to data analysis and graphical presentation in biostatistics with R[electronic resource] :statistics in the large /
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Excel 2010 for engineering statistics[electronic resource] :a guide to solving practical problems /
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Penalty, shrinkage and pretest strategies[electronic resource] :variable selection and estimation /
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Bayesian statistics from methods to models and applications[electronic resource] :research from BAYSM 2014 /
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Regression modeling strategies[electronic resource] :with applications to linear models, logistic and ordinal regression, and survival analysis /
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Vector generalized linear and additive models[electronic resource] :with an implementation in R /
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Humanities data in R[electronic resource] :exploring networks, geospatial data, images, and text /
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Model-free prediction and regression[electronic resource] :a transformation-based approach to inference /
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Excel 2013 for engineering statistics[electronic resource] :a guide to solving practical problems /
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Statistical analysis and data display[electronic resource] :an intermediate course with examples in R /
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Introduction to statistics[electronic resource] :using interactive MM*Stat elements /
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Modern methodology and applications in spatial-temporal modeling[electronic resource] /
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Foundations and methods in combinatorial and statistical data analysis and clustering[electronic resource] /
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Multivariate time series with linear state space structure[electronic resource] /
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Recent advances in natural computing[electronic resource] :selected results from the IWNC 8 Symposium /
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Statistical analysis for high-dimensional data[electronic resource] :The Abel Symposium 2014 /
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Data mining with SPSS modeler[electronic resource] :theory, exercises and solutions /
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A course in mathematical statistics and large sample theory[electronic resource] /
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Excel 2016 for business statistics[electronic resource] :a guide to solving practical problems /
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Excel 2016 for biological and life sciences statistics[electronic resource] :a guide to solving practical problems /
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Algorithmic advances in Riemannian geometry and applications[electronic resource] :for machine learning, computer vision, statistics, and optimization /
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Essentials of Excel, Excel VBA, SAS and Minitab for statistical and financial analyses[electronic resource] /
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Recent advances in robust statistics[electronic resource] :theory and applications /
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Beginning SQL Server R Services[electronic resource] :analytics for data scientists /
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