R is a programming language and free software environment for statistical computing and graphics. The R programming language is one of the most important tools for any statistician in the 21st century. R language is widely used among statisticians and data miners for developing statistical software and data analysis. As a programming language, R supports various programming paradigms including array, functional, procedural, reflective, imperative and object-oriented programming.
Some
of the common statistical features of R include linear and nonlinear modeling,
classical statistical tests, time-series analysis, classification and
clustering. It is not however limited to only these and actually one of the
strengths of R lies in its ability to produce quality static images and graphs
with mathematical functions.
More
often than not, students of statistics have had trouble with R programming and
mainly this is due to the fact that statistics is considered to be more of a
mathematics oriented course. These students therefore in most cases end up
having trouble with programming concepts. Just like any other programming
language, being good at R programming requires constant programming practice
which in most cases you may not have time to as a student
.
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When
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help, we not only write code solutions but we also document explanations
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work, they can be used to provide explanations.
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