Bayesian analysis with Excel and R / Conrad G. Carlberg.
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Item type | Current library | Home library | Collection | Shelving location | Call number | Status | Date due | Barcode |
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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 |
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GC QA 76.585 D56 2022 Exam ref AZ-500 : Microsoft Azure security technologies / | GC QA 76.585 P58 2022 Exam ref AZ-700 designing and implementing microsoft azure networking solutions / | GC QA 76.774 M34 2014 Unix in easy steps / | GC QA 279.5 C37 2023 Bayesian analysis with Excel and R / | GC QA 845 L66 1923 An elementary treatise on the dynamics of a particle and of rigid bodies / | GC TK 5105.5 B33 2022 CCNP and CCIE enterprise core ENCOR 350-401 Exam Cram | GC TK 7968 E24 2021 Eagle tutorial for beginners : eagle software introduction / |
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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