A Course in Statistics with R - Hardcover

Tattar, Prabhanjan N.; Ramaiah, Suresh; Manjunath, B. G.

Hardcover

ISBN 10: 1119152720 ISBN 13: 9781119152729

Publisher: Wiley, 2016

Synopsis

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 this title

About the Author

Prabhanjan Tattar , Business Analysis Senior Advisor at Dell International Services, Bangalore, India. Professor Tattar is a statistician providing analytical solutions to business problems inclusive of statistical models and machine learning as appropriate.

Suresh Ramaiah, Assistant Professor of Statistics at Dharwad University, Dharwad, India.

B G Manjunath, Business Analysis Advisor at Dell International Services, Bangalore, India

From the Back Cover

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

From the Inside Flap

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

Edition details

• Publisher: Wiley
• Publication date: 2016
• Language: English
• ISBN 10: 1119152720
• ISBN 13: 9781119152729
• Binding: Hardcover
• Edition number: 1
• Number of pages: 696