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Bayesian Analysis with Excel and R

of Excel's Bayesian capabilities and move toward R to do even more. Step by step, with real-world examples, Carlberg shows you how to use;

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Bayesian Analysis Made Simple

GLMMs and beyond, Bayesian Analysis Made Simple describes how to use Excel for a vast range of Bayesian models in an intuitive manner accessible;

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Bayesian Analysis Made Simple

and beyond, Bayesian Analysis Made Simple describes how to use Excel for a vast range of Bayesian models in an intuitive manner accessible to;

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Bayesian Approaches in Oncology Using R and OpenBUGS

Bayesian Approaches in Oncology Using R and OpenBUGS serves two audiences: those who are familiar with the theory and applications;

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Bayesian Population Analysis using WinBUGS

steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R ;

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Introduction to Bayesian Estimation and Copula Models of Dependence

Excel(R), basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference;

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Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods;

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Doing Bayesian Data Analysis

Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first;

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Doing Bayesian Data Analysis

Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian;

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Financial Analysis with Microsoft Excel

with Mayes' FINANCIAL ANALYSIS WITH MICROSOFT (R) EXCEL (R), 9E. This edition provides a reader-friendly solid foundation in corporate finance;

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Computational Bayesian Statistics

underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes. The unique features of the;

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Computational Bayesian Statistics

underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes. The unique features of the;

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Biostatistics

The book includes extensive problem sets and references in each chapter, as well as complete instructions on computer analysis with the;

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Bayesian Essentials with R

readily understandable and expandable. Bayesian Essentials with R can be used as a textbook at both undergraduate and graduate levels. It;

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Advancing into Analytics

about data manipulation into R and Python programming. This practical book guides you through: Foundations of analytics in Excel: Use;

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Statistics with Microsoft Excel

Statistics with Microsoft Excel, Fifth Edition, shows readers how to use Microsoft Excel (R) to perform statistical analysis. This step-by;

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Bayesian Statistics for the Social Sciences

Bridging the gap between traditional classical statistics and a Bayesian approach, David Kaplan provides readers with the concepts and;

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the;

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Bayesian Analysis of Infectious Diseases

Bayesian Analysis of Infectious Diseases -COVID-19 and Beyond shows how the Bayesian approach can be used to analyze the evolutionary;

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Corporate Financial Analysis with Microsoft Excel

. Corporate Financial Analysis with Microsoft (R)Excel (R) is the ideal tool for managing yourfirm's short-term operations and long-termcapital;

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Bayesian Analysis with R for Drug Development

, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems;

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Bayesian Analysis with R for Drug Development

, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, describes a wide range of Bayesian applications to problems;

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Bayesian Hierarchical Models

and data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal;

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Bayesian Hierarchical Models

data analysis, but now using entirely R-based Bayesian computing options. It has been updated with a new chapter on regression for causal;

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Bayesian Model Selection and Statistical Modeling

Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model;

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Statistics with Microsoft Excel

Key Message: Statistics with Microsoft Excel (R), Fourth Edition shows readers how to use Microsoft Excel(R) to perform statistical;

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Bayesian Analysis For Social Sciences

implement the methods using WinBUGS - the most-widely used Bayesian analysis software in the world - and R - an open-source statistical software;

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