Name: Introductory Statistics With r (Statistics and Computing) (en Inglés)
Price: 232.38 PEN
Availability: InStock
Author: Dalgaard, Peter
ISBN: 9780387790534

portada Introductory Statistics With r (Statistics and Computing) (en Inglés)

Formato

Libro Físico

Autor

Peter Dalgaard

Editorial

Springer

Año

2008

Idioma

Inglés

N° páginas

364

Encuadernación

Tapa Blanda

Dimensiones

23.5 x 15.8 x 1.8 cm

Peso

0.54 kg.

ISBN

0387790535

ISBN13

9780387790534

N° edición

0002

Categorías

Anatomía
Fisiologiía
Probabilidad y estadística
Biología
Software de matemáticas y estadísticas

Introductory Statistics With r (Statistics and Computing) (en Inglés)

Peter Dalgaard (Autor) · Springer · Tapa Blanda

Libro Nuevo

S/ 232,38

S/ 464,76

Ahorras: S/ 232,38

50% descuento

Envío normal

Origen: España (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Martes 21 de Mayo y el Jueves 30 de Mayo.

Lo recibirás en cualquier lugar de Perú entre 2 y 5 días hábiles luego del envío.

Reseña del libro "Introductory Statistics With r (Statistics and Computing) (en Inglés)"

R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development. 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. A supplementary R package can be downloaded and contains the data sets. The statistical methodology 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 six chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, survival analysis, Poisson regression, and nonlinear regression. In the second edition, the text and code have been updated to R version 2.6.2. The last two methodological chapters are new, as is a chapter on advanced data handling. The introductory chapter has been extended and reorganized as two chapters. Exercises have been revised and answers are now provided in an Appendix.