PACKT R STATISTICAL APPLICATION DEVELOPMENT BY EXAMPLE BEGINNERS GUIDE 2013 RETAIL EBOOK-kE

TITLE: R STATISTICAL APPLICATION DEVELOPMENT BY EXAMPLE

BEGINNER'S GUIDE

PUBLISHER: PACKT LANGUAGE: ENGLISH

LINK: http://is.gd/XJhO62 RELEASE TYPE: RETAIL

FORMAT: PDF RELEASE DATE: 2013.11.23

ISBN: 9781849519441 STORE DATE: 2013

SAVED.MONEY: 40 DOLLAR DISKCOUNT: 03 x 05MB

AUTHOR: PRABHANJAN NARAYANACHAR TATTAR



BOOK



Learn R Statistical Application Development from scratch in a

clear and pedagogical manner



Overview

A self-learning guide for the user who needs statistical

tools for understanding uncertainty in computer science data

Essential descriptive statistics, effective data visualization

and efficient model building. Every method explained through

real data sets enables clarity and confidence for unforeseen

scenarios

In Detail



"R Statistical Application Development by Example Beginner's

Guide" explores statistical concepts and the R software, which

are well integrated from the word go. This demarcates the

separate learning of theory and applications and hence the title

begins with "R Statistical .". Almost every concept has an R code

going with it which exemplifies the strength of R and

applications. Thus, the reader first understands the data

characteristics, descriptive statistics, and the exploratory

attitude which gives the first firm footing of data analysis

Statistical inference and the use of simulation which makes use

of the computational power complete the technical footing of

statistical methods. Regression modeling, linear, logistic, and

CART, builds the essential toolkit which helps the reader

complete complex problems in the real world



The reader will begin with a brief understanding of the nature of

data and end with modern and advanced statistical models like

CART. Every step is taken with DATA and R code



The data analysis journey begins with exploratory analysis, which

is more than simple descriptive data summaries, and then takes

the traditional path up to linear regression modeling, and ends

with logistic regression, CART, and spatial statistics



True to the title R Statistical Application Development by

Example Beginner's Guide, the reader will enjoy the examples and

R software



What you will learn from this book

Learn the nature of data through software which takes the

preliminary concepts right away in R Read data from various

sources and export the R output to other software Perform

effective data visualization which respects the nature of

variables and with rich alternative options Do exploratory data

analysis for useful first understanding which builds up the right

attitude towards effective inference Learn statistical

inference through simulation combining the classical inference

and modern computational power Delve deep into regression

models such as linear and logistic for continuous and discrete

regressands which form the fundamentals of modern statistics

Introduce yourself to CART - a machine learning tool which is

very useful when the data has an intrinsic nonlinearity