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

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 							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
  						

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