A course in statistics with R

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, non-parametric, 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.

Machine generated contents note: pt. I THE PRELIMINARIES -- 1.Why R? -- 1.1.Why R? -- 1.2.R Installation -- 1.3.There is Nothing such as PRACTICALS -- 1.4.Datasets in R and Internet -- 1.4.1.List of Web-sites containing DATASETS -- 1.4.2.Antique Datasets -- 1.5.http://cran.r-project.org -- 1.5.1.http://r-project.org -- 1.5.2.http://www.cran.r-project.org/web/views/ -- 1.5.3.Is subscribing to R-Mailing List useful? -- 1.6.R and its Interface with other Software -- 1.7.Help and/or? -- 1.8.R Books -- 1.9.A Road Map -- 2.The R Basics -- 2.1.Introduction -- 2.2.Simple Arithmetics and a Little Beyond -- 2.2.1.Absolute Values, Remainders, etc. -- 2.2.2.round, floor, etc. -- 2.2.3.Summary Functions -- 2.2.4.Trigonometric Functions -- 2.2.5.Complex Numbers -- 2.2.6.Special Mathematical Functions -- 2.3.Some Basic R Functions -- 2.3.1.Summary Statistics -- 2.3.2.is, as, is.na, etc. -- 2.3.3.factors, levels, etc. -- 2.3.4.Control Programming -- 2.3.5.Other Useful Functions

Note continued: 2.3.6.Calculus* -- 2.4.Vectors and Matrices in R -- 2.4.1.Vectors -- 2.4.2.Matrices -- 2.5.Data Entering and Reading from Files -- 2.5.1.Data Entering -- 2.5.2.Reading Data from External Files -- 2.6.Worki…