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Text Analysis with R

Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source;

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R Book

that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R. (The American;

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Mastering Text Mining with R

Master text-taming techniques and build effective text-processing applications with R About This Book * Develop all the relevant;

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R for Marketing Research and Analytics

modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a;

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Applied Meta-Analysis with R and Stata

without having to plough through theorems and proofs. -Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second;

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Applied Meta-Analysis with R and Stata

without having to plough through theorems and proofs. -Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second;

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Research Methods And Data Analysis In The Social Sciences

of observation, survey, and experiment, the text pairs each method chapter with a chapter on the analysis of the types of results usually obtained with;

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Analyzing Textual Information

Researchers in the social sciences and beyond are dealing more and more with massive quantities of text data requiring analysis, from;

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Applied Power Analysis for the Behavioral Sciences

limited quantitative backgrounds. With practical use in mind, the text provides detailed coverage of topics such as how to estimate expected;

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Statistics and Data Analysis for Microarrays Using R and Bioconductor

Ontology analysis, pathway analysis, and machine learning techniques. Methods are illustrated with toy examples and real data and the R code for;

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Computational Statistics

software package for data analysis, statistical programming, and graphics. Integrating R code and examples throughout, the text only requires basic;

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Making Hard Decisions with DecisionTools

for risk and decision analysis. At the end of each chapter, topics are illustrated with step-by-step instructions for DecisionTools (R). This;

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Robust Multivariate Analysis

published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics;

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Graphical Data Analysis with R

See How Graphics Reveal Information Graphical Data Analysis with R shows you what information you can gain from graphical displays. The;

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Graphical Data Analysis with R

See How Graphics Reveal Information Graphical Data Analysis with R shows you what information you can gain from graphical displays. The;

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Engineering Vibration

analysis, and the use of MATLAB(R), Mathcad(R), or Mathematica(R). The author provides an unequaled combination of the study of conventional;

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Engineering Vibrations

analysis, and the use of MATLAB (R), Mathcad (R), or Mathematica (R). The author provides an unequaled combination of the study of conventional;

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Analysis of Categorical Data with R

Learn How to Properly Analyze Categorical DataAnalysis of Categorical Data with R presents a modern account of categorical data analysis;

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Biostatistics with R: An Introduction to Statistics Through Biological Data

, hypothesis testing, linear regression analysis, and clustering with two appendices on installing and using R and R-Commander. A novel feature of this;

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Biostatistics for Epidemiology and Public Health Using R

sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses;

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An Introduction to R for Spatial Analysis and Mapping

" ""In an age of big data, data journalism and with a wealth of quantitative information around us, it;

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Introductory Statistics with R

methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way;

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Numerical Methods

that have practical applications. The authors' approach is to integrate MATLAB (R) with numerical analysis in a way which adds clarity to the;

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Text Analytics for Business Decisions

With the rise in data science development, we now have many remarkable techniques and tools to extend data analysis from numeric and;

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A Primer in Biological Data Analysis and Visualization Using R

R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;

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A Primer in Biological Data Analysis and Visualization Using R

R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;

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R and Data Mining

, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more. Data;

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