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.
If
you are having trouble with your R programming assignments then Statistics
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At
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Some
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When
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explanations of how these solutions came up and why the assignment is done in a
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presentations of their work, they can be used to provide explanations.
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