R Programming is an influential statistical programming language widely used for analytical modeling and other data mining related methods. It can be used for data aggregation, data manipulation, statistical modeling, Creating charts and plots. It is a programming language which requires no pre-requisites unlike the other programming languages. There are many remarkable packages available in R programing training that will help in a brief data examination. The advantages of this program are:
It includes all of the standard statistical tests, models and analyses, as well as provides a complete language for managing and operating data.
- It is a programming language developed for statistical analysis by practicing statisticians and assistants. It imitates well on a very competent community of computational statisticians.
- Its graphical capabilities are outstanding, providing a completely programmable graphics language that exceeds most other statistical and graphical packages.
- As it is an open source, it has been studied by many worldwide renowned statisticians and computational scientists.
- It allows anyone to use and modify it. R is approved under the GNU General Public License.
- It has over 4800 packages available from numerous repositories specializing in topics like data mining.
- Econometrics, spatial analysis and bio-informatics.
- It is cross-platform and runs on various operating systems and different hardware. It is widely used on Macintosh, GNU/Linux and Microsoft Windows, running on both 32 & 64 bit processors.
- It plays well with many other tools, introducing data, for example, from CSV les, SAS and SPSS, or directly from Microsoft Access, Microsoft Excel, Oracle, MySQL and SQLite. It can also create graphics output in JPG, PDF, PNG, SVG formats and table output for LATEX and HTML.
Business analytics course is specifically designed with substantial knowledge of statistics that help aspirants to have a bright career in data Analytics. It is also a widely used tool in many big organizations like top Banks, Retail, IT, Healthcare, Supply chain and logistics firms. This course is appropriate for:
Web developers who want to use data analysis features in their webpage
- Anyone interested in statistics and data sciences
- Students who perform data analysis including graphs
- Professionals working in analytics or associated fields
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