Bayesian analysis with Excel and R / Conrad G. Carlberg.

By: Carlberg, Conrad George [author.]Material type: TextTextPublisher: [Upper Saddle River, New Jersey?] : Pearson Education, Inc., c2023Copyright date: ©2023Description: xvi, 169 pages : illustrations ; 24 cmISBN: 978-0-13-758098-9Subject(s): MICROSOFT EXCEL (COMPUTER FILE) | MICROSOFT EXCEL (COMPUTER FILE) | BAYESIAN STATISTICAL DECISION THEORY | (COMPUTER PROGRAM LANGUAGE) RDDC classification: 519.5/42 LOC classification: QA 279.5 C37 2023
Contents:
Chapter 1 : Bayesian Analysis and R: An Overview. -- Chapter 2 : Generating Posterior Distributions with the Binomial Distribution. -- Chapter 3 : Understanding the Beta Distribution. -- Chapter 4 : Grid Approximation and the Beta Distribution. -- Chapter 5 : Grid Approximation with Multiple Parameters. -- Chapter 6 : Regression Using Bayesian Methods. -- Chapter 7 : Handling Nominal Variables. -- Chapter 8 : MCMC Sampling Methods. --
Summary: "Leverage the full power of Bayesian analysis for competitive advantage. Bayesian methods can solve problems you can't reliably handle any other way. Building on your existing Excel analytics skills and experience, Microsoft Excel MVP Conrad Carlberg helps you make the most 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 Bayesian analytics to solve a wide array of real problems. Carlberg clarifies terminology that often bewilders analysts, provides downloadable Excel workbooks you can easily adapt to your own needs, and offers sample R code to take advantage of the rethinking package in R and its gateway to Stan. As you incorporate these Bayesian approaches into your analytical toolbox, you'll build a powerful competitive advantage for your organization--and yourself."--Page 4 of cover.
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Item type Current library Home library Collection Shelving location Call number Status Date due Barcode
Books Books NU Fairview College LRC
NU Fairview College LRC
School of Engineering and Technology Technical Services GC QA 279.5 C37 2023 (Browse shelf(Opens below)) Available NUFAI000005842

Includes index.

Chapter 1 : Bayesian Analysis and R: An Overview. -- Chapter 2 : Generating Posterior Distributions with the Binomial Distribution. -- Chapter 3 : Understanding the Beta Distribution. -- Chapter 4 : Grid Approximation and the Beta Distribution. -- Chapter 5 : Grid Approximation with Multiple Parameters. -- Chapter 6 : Regression Using Bayesian Methods. -- Chapter 7 : Handling Nominal Variables. -- Chapter 8 : MCMC Sampling Methods. --

"Leverage the full power of Bayesian analysis for competitive advantage. Bayesian methods can solve problems you can't reliably handle any other way. Building on your existing Excel analytics skills and experience, Microsoft Excel MVP Conrad Carlberg helps you make the most 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 Bayesian analytics to solve a wide array of real problems. Carlberg clarifies terminology that often bewilders analysts, provides downloadable Excel workbooks you can easily adapt to your own needs, and offers sample R code to take advantage of the rethinking package in R and its gateway to Stan. As you incorporate these Bayesian approaches into your analytical toolbox, you'll build a powerful competitive advantage for your organization--and yourself."--Page 4 of cover.

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