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Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: 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. Codice inventario libreria

Su questo libro:

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Riassunto:

This guide assumes no prior knowledge, and starts by introducing you to the very first principles of statistics in R before progressing to more advanced concepts of application development through instructive screenshots and examples.

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

Approach

Full of screenshots and examples, this Beginner’s Guide by Example will teach you practically everything you need to know about R statistical application development from scratch.

Who this book is written for

You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject.

Sinossi:

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

Approach

Full of screenshots and examples, this Beginner’s Guide by Example will teach you practically everything you need to know about R statistical application development from scratch.

Who this book is written for

You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject.

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Descrizione libro Packt Publishing Limited, United Kingdom, 2013. Paperback. Condizione libro: New. 230 x 192 mm. Language: English Brand New Book ***** Print on Demand *****.Full of screenshots and examples, this Beginner s Guide by Example will teach you practically everything you need to know about R statistical application development from scratch. You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject. Codice libro della libreria AAV9781849519441

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Descrizione libro Packt Publishing Limited, United Kingdom, 2013. Paperback. Condizione libro: New. 230 x 192 mm. Language: English . Brand New Book ***** Print on Demand *****. Full of screenshots and examples, this Beginner s Guide by Example will teach you practically everything you need to know about R statistical application development from scratch. You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject. Codice libro della libreria AAV9781849519441

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Descrizione libro Packt Publishing Limited. Paperback. Condizione libro: New. Paperback. 344 pages. Dimensions: 9.1in. x 7.6in. x 0.9in.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 Beginners 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 Beginners 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 Approach Full of screenshots and examples, this Beginners Guide by Example will teach you practically everything you need to know about R statistical application development from scratch. Who this book is written for You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Paperback. Codice libro della libreria 9781849519441

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