A Course in Statistics with R - Hardcover

9781119152729: A Course in Statistics with R
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Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models.

Key features:

  • Integrates R basics with statistical concepts
  • Provides graphical presentations inclusive of mathematical expressions
  • Aids understanding of limit theorems of probability with and without the simulation approach
  • Presents detailed algorithmic development of statistical models from scratch
  • Includes practical applications with over 50 data sets

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From the Back Cover:
A Course in Statistics with R
Prabhanjan Narayanachar Tattar, Fractal Analytics Inc, India
Suresh Ramaiah, Karnatak University, India
B.G. Manjunath, Dell International Services, India

Integrates the theory and applications of statistics using R 

A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs.  The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject.  With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis.  Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation.  Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models.
Key features:
  • Integrates R basics with statistical concepts
  • Provides graphical presentations inclusive of mathematical expressions
  • Aids understanding of limit theorems of probability with and without the simulation approach
  • Presents detailed algorithmic development of statistical models from scratch
  • Includes practical applications with over 50 data sets
About the Author:
Prabhanjan Tattar is working as a Lead Statistician and Manager at Ford Motor Company. He is also author of the books Statistical Application Development with R and Python, 2e, by Packt Publication, and Practical Data Science Cookbook, 2e, by Packt. Survival Analysis and Machine Learning are his areas of research interest.

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  • PublisherWiley
  • Publication date2016
  • ISBN 10 1119152720
  • ISBN 13 9781119152729
  • BindingHardcover
  • Edition number1
  • Number of pages696

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Book Description Hardcover. Condition: new. Hardcover. Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models. Key features: Integrates R basics with statistical conceptsProvides graphical presentations inclusive of mathematical expressionsAids understanding of limit theorems of probability with and without the simulation approachPresents detailed algorithmic development of statistical models from scratchIncludes practical applications with over 50 data sets Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781119152729

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