LEARNING R PROGRAMMING LANGUAGE FOR ECONOMICS

Sorin Teiusan

Annals - Economy Series, 2023, vol. 4, 58-79

Abstract: Worldwide, scientists conduct research finding answers to questions, and that to do this they have to use, measure, and analyze data. Nowadays, more than never, computer programs are intensive used by researchers from various domains in order to ahieve their goals. There are different software helping scholars to get research results. R is currently one of the top programming languages preferred for accomplishing data science. Descending from the S programming language, R is an independent, open-source, and free software environment, which can be used for statistical analysis, visualization and reporting. In present, the R environment has become one of the most used statistical analysis tools, being used in university and academic research environments, but also in the business environment. More and more companies are using R as a data analysis tool. R is also supported by the academic community. The world's major universities support R. R is being used in the disciplines of finance, banking, insurance, economics, stock market, marketing, computer science, and many other disciplines and fields. Specialists in these fields need R knowledge and skills to analyze data. This article promotes learning of R programming language by students, researchers, and teachers from economic field. Learning R programming language is the acquisition of information, knowledge, and skills of R software. It is an ongoing process that takes place throughout whole professional life without an end date. Learning a programming language like R is the same as learning a spoken language? What is the difference between R and RStudio? How can we gain R skills? These are the questions we propose to answer through this research paper. The goal is helping beginners to enter into the R system. Results consist in providing information and sources to help economist and other people interested in starting learning R programming language.

Keywords: R environment; RStudio; learning; research; knowledge; skills (search for similar items in EconPapers)
Date: 2023
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