R Programming for Data Analysis: A Comprehensive Assignment

This assignment explores the application of R programming in data mining and statistical analysis. The student reflects on their learning experience, highlighting the practical uses of R for descriptive statistics, data visualization, and probabilistic modeling. The assignment discusses challenges faced, such as importing data from different formats and the need to memorize specific codes. The student contrasts R with other tools like Excel, emphasizing the need for precise coding in R. The student's career goal is to become a data analyst, and they see R as a key tool for statistical computations and design, aiming to use it to advance their career and gain relevant skills for the job market. References to Kanaracus (2012), Lam (2016), and Simon (2003) are provided.

DM W8 Post
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The technology of R is an open source language used in programming. R language as
applied in data mining is mainly for analytical purposes. Given that it is build to assist in data
analysis, the R programming language is very practical in the way it allows analysis of raw
statistical data to give a clear meaning of a data which will otherwise appear useless. In my 8
weeks learning how to conduct data mining using the R language, I have found the ability of
the technology to derive statistical meaning such as descriptive statistics, visual
representation of data and modelling of probabilistic functions to be one of the most
important practical application of the programming language (Simon, 2003). With R, past
quantitative information can now be applied toderive trends and predict some of the most
likely future occurrences.
With my experience with R am yet to come in contact with a data that is recorded in
an R format. Occasionally the data to be analyzed have to be imported from files with
formats such as excel. My first wonder is how did the developers of the R language expect to
derive the data to be analyzed if the other software like excel were not there (Lam, 2016). Or
just to say is there a way of recording a raw data in R format? In addition to this I have found
it significantly had to compute functions in R and call them. Being that functions are some of
the most applied techniques in data mining I am a bit concerned by the way this weakness
may affect my abilities to be an expert in this cause.
The use of R programming to conduct data mining is quit challenging. For instance, I
have had experience with data analysis using the excel software. In my previous case a
graphical user interface was provided. From the interface it was easy to conduct data analysis
by simply inserting functions and formulas. During my learning of the R language I have
found the frequent need to memorize codes related to various functions quit challenging. The
R language when used during analysis requires that I have an exact knowledge of the code to
be applied in each of the specific command (Kanaracus, 2012). These codes are unique and
even a slight mistake may cause an error. Compared to the excel analysis where most of the
functions are inbuilt and occasionally the software gives suggestions to help remind the user,
R programming is totally different.
My career target is to be a professional in data analyst. My study of R was inspired by
the ability of the language to enable an effective environment for statistical computations and
design. Being one of the languages that offer a wide range of statistics, I intend to make use
of R as a pathway to further my profession. By studying and having a strong grip of R I

believe I will be able to possess more than adequate skills necessary to secure a job in
analytical companies. From here its my hope that I can apply my gained knowledge to further
my career to the bet level possible.

References
Kanaracus, C. (2012). Oracle Stakes Claim in R With Advanced Analytics Launch. PC World.
Lam, J. (2016, March 22). Introducing R Tools for Visual Studio. Retrieved from The Visual Studio
Blog: https://blogs.msdn.microsoft.com/visualstudio/2016/03/22/introducing-r-tools-for-
visual-studio-3/
Simon, J. (2003). R For the Political Methodologist. The Political Methodologist. Political
Methodology Section, American Political Science Association, 20–22.