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R Integration

R codes further enhance the existing data manipulation, statistical analysis and predictive forecasting capabilities of IBM SPSS software.

What is R?
R is an opensource programming language and software environment for statistical computing and graphics. The R language is mainly popular among statisticians and data miners who use it to develop statistical programs, but it is also a widely used tool for advanced data analysis. It is capable of comprehensive statistical and graphical techniques such as linear and non-linear modelling, classical statistical tests, time series analysis, classification, and clustering for statistical computations and graphing.

Many of the available R packages specialise in econometrics, data mining, spatial analysis, bioinformatics, and other areas. It is peer-reviewed by renowned statisticians and computer scientists, but due to its opensource nature, the processes for each version and package are not strictly controlled.

SPSS Modeler and R
The R coding further enhances the software's existing data manipulation, statistical analysis, and predictive forecasting capabilities. The R add-on packages also allow the use of algorithms that do not exist in Modeler. Using R packages makes data visualization more efficient and algorithms more parameterizable.

In Modeler, you can create your nodes written in R using the Custom Node Dialog Builder. You can do the same using the Extension nodes in the palettes. The R nodes created in this way can be shared with other users who do not program their analyses but can benefit from the new facility. This allows developers to focus on writing code and users to focus on analysis while enjoying the extended R functionality without having to learn R.

Benefits of integrating R
SPSS Modeler provides a great platform for R users to analyze large data sets, and create visualizations and other outputs. An additional benefit of the integration is the ease of use of Modeler and the ability to share integrated R packages with colleagues who are not familiar with programming.

In the case of R, due to the lack of formal marketing, there is no quality assurance, so it can only be used at your own risk and there is no guarantee that its functions will work properly. However, Modeler, as IBM software, is subject to a rigorous quality assurance process that guarantees the security of corporate data.

R users get excellent data management, a visual interactive interface, presentation-quality output and advanced scalability with SPSS software, and SPSS users get a rich, ever-expanding toolkit for a deeper understanding of their data.

What industries can it be used in?

Financial services
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