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The R language is a programming language that has an instruction system suitable for statistical analysis. It is an interpreted language, and one of its features is that it operates on multiple platforms.
It is also an open-source and free language, so anyone can easily set up the same working environment.
The R language is a programming language that specializes in statistical Data analysis. It is not a general-purpose language that can handle any program, like C, Java, or the popular Python.
On the other hand, because it has an excellent function of performing Data analysis and outputting it to graphs, you can easily program the output of various graphs.
The R language is often used in the fields of applied statistics, such as financial engineering and machine learning.
Packages specialized in the field of life science are also often used. In particular, the field of machine learning is closely related to AI, so companies that perform big Data analysis are also introducing this, and the number of people learning is increasing.
There are many advantages of the R language. First of all, it has many useful functions for Data analysis.
Not only that, but many packages are also available, so you can use them as needed.
Machine learning and big Data analysis are attracting attention, so demand is also increasing.
Here, let's focus on what can be achieved with the R language. What kind of benefits will statistical analysis and Data analysis in R language bring to the real world?
Taking the business world as an example, Data analysis and visualization support decision-making are available across industries.
Utilization methods such as sales forecasting, factor analysis, and verification of the effectiveness of measures are pervading corporate management in terms of business intelligence (BI) and business Analytics (BA).
As introduced earlier, the R language plays an active role in statistical analysis.
Statistical models such as forecasting and optimization have been developed around risk calculation and forecasting in fields such as finance and aerospace.
It is also useful for optimal allocation of costs and personnel, evaluation of measures, diagnosis and detection, and optimization of inventory.
In recent years, machine learning and AI models have also come to be used in actual business, and it can be said that the R language is widely used in AI-related work.
The R language implements many functions specialized for statistical analysis internally, but you can also use the functions obtained through CRAN.
You can also program it in C or FORTRAN and call and use externally compiled functions.
Occupations that contribute to business through Data analysis and statistical techniques are called Data scientists.
The R language is a well-known tool that is often used along with Python in the Data analysis they promote.
Machine learning and AI have become a boom. The R language also plays an active role in occupations and research institutes that promote Data engineering, such as machine learning engineers.