Introductory statistics with R /
Dalgaard, Peter.
Introductory statistics with R / Peter Dalgaard. - 2nd ed. - New York : Springer, c2008. - xvi, 363 p. : ill. ; 24 cm. - Statistics and computing, 1431-8784 .
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.
Includes bibliographical references (p. [355]-356) and index.
Basics --
The R environment --
Probability and distributions --
Descriptive statistics and graphics --
One- and two-sample tests --
Regression and correlation --
Analysis of variance and the Kruskal-Wallis test --
Tabular data --
Power and the computation of sample size --
Advanced data handling --
Multiple regression --
Linear models --
Logistic regression --
Survival analysis --
Rates and Poisson regression --
Nonlinear curve fitting.
9780387790534 0387790535
Statistics
Mathematical statistics
Bioinformatics
Mathematical & Statistical Software
Probability & Statistics
R (Computer program language)--Data processing.
519.502 / DAL
Introductory statistics with R / Peter Dalgaard. - 2nd ed. - New York : Springer, c2008. - xvi, 363 p. : ill. ; 24 cm. - Statistics and computing, 1431-8784 .
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.
Includes bibliographical references (p. [355]-356) and index.
Basics --
The R environment --
Probability and distributions --
Descriptive statistics and graphics --
One- and two-sample tests --
Regression and correlation --
Analysis of variance and the Kruskal-Wallis test --
Tabular data --
Power and the computation of sample size --
Advanced data handling --
Multiple regression --
Linear models --
Logistic regression --
Survival analysis --
Rates and Poisson regression --
Nonlinear curve fitting.
9780387790534 0387790535
Statistics
Mathematical statistics
Bioinformatics
Mathematical & Statistical Software
Probability & Statistics
R (Computer program language)--Data processing.
519.502 / DAL