Libros UCLV { BETA }

Estadística computacional

The high-level language of R is recognized as one of the most powerful and flexible statistical software environments, and is rapidly becoming the standard setting for quantitative analysis, statistics and graphics. R provides free access to unrivalled coverage and cutting-edge applications, enabling the user to apply numerous statistical methods ranging from simple regression to time series or multivariate analysis. Building on the success of the author’s bestselling Statistics: An Introduction using R, The R Book is packed with worked examples, providing an all inclusive guide to R, ideal for novice and more accomplished users alike. The book assumes no background in statistics or computing and introduces the advantages of the R environment, detailing its applications in a wide range of disciplines. Provides the first comprehensive reference manual for the R language, including practical guidance and full coverage of the graphics facilities. Introduces all the statistical models covered by R, beginning with simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression and analysis of variance, through to generalized linear models, generalized mixed models, time series, spatial statistics, multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates and professionals in science, engineering and medicine. It is also ideal for students and professionals in statistics, economics, geography and the social sciences.

The book is intended for students, researchers and practitioners both in and out of academia. However, no prior knowledge of statistics is assumed. Consequently, the presentation moves from very basic (but not simple) to sophisticated. Even if you know statistics and R, you may find the many many examples with a variety of real world data, graphics and analyses useful. You may use the book as a reference and, to that end, we include two extensive indices. The book includes (almost) parallel discussions of analyses with the normal density, proportions (binomial), counts (Poisson) and bootstrap methods.

Chapter 1 Introduction Statistics is fundamentally concerned with the understanding of structure in data. One of the effects of the information-technology era has been to make it much easier to collect extensive datasets with minimal human intervention. Fortunately, the same technological advances allow the users of statistics access to much more powerful ‘calculators’ to manipulate and display data. This book is about the modern developments in applied statistics that have been made possible by the widespread availability of workstations with high-resolution graphics and ample computational power. Workstations need software, and the S 1 system developed at Bell Laboratories (Lucent Technologies, formerly AT&T) provides a very flex- ible and powerful environment in which to implement new statistical ideas. Lu- cent’s current implementation of S is exclusively licensed to the Insightful Cor- poration 2 , which distributes an enhanced system called S-PLUS . An Open Source system called R 3 has emerged that provides an independent implementation of the S language. It is similar enough that almost all the exam- ples in this book can be run under R .

Trabajo práctico con el software estadístico SPSS

Cubre los temas normas generales del SPSS, estadística descriptiva unidimensional, relación entre dos variables, Probabilidad y variables aleatorias, Contrastes paramétricos y no paramétricos.

Análisis estadístico de datos usando SPSS

This document is intended to help you draw conclusions from your data by statistically analysing it using SPSS (Statistical Package for the Social Sciences).

Análisis estadístico en SPSS

Cubre los temas de estadística descriptiva, distribuciones de probabilidades y contrastes de hipótesis y análisis de varianza, regresión y series temporales

Guía práctica de trabajo con SPSS que cubre los temas de trabajo con las variables, distribución de frecuencias, medidas de tendencia central, dispersión y forma, prueba de T-Student, Chi cuadrado, análisis de varianza, regresión, correlación y determinación simple, diseños DCA y DBCA