Develop, Document and Publish R-Projects in Microsoft Excel and Word

Inference for R enables you to use the familiar Microsoft Excel and Word environment to assemble dynamic documents containing your data, R software objects, R commands, and text annotations (commentary). When executed, a dynamic document runs R commands and generates a results document that contains textual, numerical and graphic output of R commands in addition to formatted text annotations. Results documents are useful for documenting your R work, creating standardized analyses, explaining and illustrating concepts with R, and publishing and sharing your results.

A research publication based on R computation is not the scholarly contribution itself; it is merely an advertisement of the scholarly contribution. The actual scholarly contribution is comprised of data, a software environment, and the complete set of instructions used to generate its figures and tables. Inferences for R enables reproducible research by giving the reader direct access to both data and software code, allowing them to thoroughly explore and reproduce the scholarly contribution. This paradigm is based on the ideas of literate programming and literate data analysis. And, Inference for R provides Inference Studio, an integrated development environment (IDE) analogous to Microsoft’s Visual Studio, which makes it easy to assemble and debug your R code.

R provides Sweave for embedding R code in LaTEX documents to create dynamic reports, which can be updated automatically if the data or analysis changes. However, to use Sweave functions requires a steep learning curve involving LaTex text formatting syntax and Sweave procedures. Sweave also makes it difficult to collaborate with colleagues who may not be familiar with LaTEX and Journals may not accept submissions in LaTEX format. By contrast, Inference for R enables you to achieve results immediately using the familiar WYSIWYG editing environment of Microsoft Word and Excel. Furthermore, Inference for R enables you to use the full data management and publishing capabilities of Microsoft Excel and Word to deliver better reports of your R-projects with less time and effort.

Inference for R is used in diverse applications including the following: univariate and multivariate data analysis and statistics, numerical analysis, data visualization, data modeling, numerical simulation and optimization, Bayesian inference, cluster analysis, computational econometrics, environmetrics, experimental design, empirical finance, statistical genetics, machine and statistical learning, natural language processing, analysis of pharmacokinetic data, psychometric models and methods, robust statistical methods, statistics for the social sciences, analysis of spatial data, survival analysis, and quality-by-design.

Leading academicians are using Inference for R to develop, document and publish their research work in statistics, science, engineering, social sciences, financial engineering, economics, and other areas. Inference for R is also used by the academic community to assist in the teaching of core courses and development of quantitative problem-solving skills. Additionally, Inference for R is being used in non-academic environments, such as government agencies and various businesses, ranging from small firms to large multinational corporations, in industries like telecommunications, financial services, statistical consulting, life sciences, clinic trial design and reporting, marketing predictive analytics and manufacturing.

 

A free 60-day fully-functional trial of Inference for R is now available.  Download your free trial today!