Take advantage of R programme

By Hellen Namawejje, :: 10-04-2012

   Many courses at the university, if not all, have a project/research paper which requires research methods and data analysis. It is the paper that carries most credit units (5) because it requires a lot of independent

    Research is a detailed study of a subject, especially in order to discover (new) information or reach a (new) understanding. It is systematic and purposive investigation of a phenomenon with respect to its nature, causes, effects and possible future implications.
    There are two broad categories of research: Qualitative and quantitative research.Qualitative research is collecting, analysing, and interpreting data by observing what people do
and say. Whereas, quantitative research refers to counts and measures of things, qualitative research refers to the meanings, concepts, definitions, characteristics, metaphors, symbols, and descriptions of things.
     There are many different ways to analyse your research data using computer languages like C/C++, PHP, VB.NET, Java, JavaScript, Silverlight, Python, and Visual Basic 6.0, among others. Most of these programmes are expensive and a lot of training centres have opened up all over the country to help academicians, researchers and students acquire skills for their use. Learning SPSS costs a minimum ofShs 300,000 for two weeks, yet there are some free computer language packages that just need a bit of effort to learn without paying that much. Besides, they are easy to access.
     However, there is a new, powerful and free online package called R. R is a powerful and free statistical environment and programming language/tool. Its extensive feature set can be enhanced by installing additional packages. It has an active user-base and detailed documentation.   
    Quantitative data analysis can be done by using the Statistical Package for the Social Sciences (SPSS). Although SPSS is a powerful tool and is comparatively easy to use, R is an alternative for researchers who do not have access to SPSS but wish to do quantitative work.
     R is a powerful statistical environment and programming language which can be used to perform statistical analyses. It produces high quality graphics from your collected data so that you can easily interprete your results. It is actively supported as there is a lot of literature written so that  anyone can teach him/herself. It also integrates well with excel especially if you want to transfer your data from Microsoft Excel.
   R is a cross-platform application and runs on Windows, Mac OS X and GNU/Linux. It is an attractive feature for those researchers who cannot afford to sponsor themselves to learn other packages since it may be freely downloaded from the Internet.
   At UCU’s  Faculty of Science and Technology, the third-year Bachelor of Computational Science students  can tell you more about R, because they have learnt it in the last two semesters when doing mathematical modelling and data analysis as their core course.  These students will be leaving campus when they already know how to analyse data. Many fields  in the real world today require data analysts and employers always check on people’s CV’s to see if you are familiar with any computer package.
    R users need to be familiar with at least  matrices (array of numbers) to fully benefit from R’s programming flexibility. Also to note is that like any other computer languages, its expressions and commands are case-sensitive. It really depends on what analysis you want to perform, what data you want to work on, and whether R offers you solutions to what you cannot accomplish in SAS, Stata, or SPSS.
There are some procedures out there you may know when interpreting data. However, what those standard statistical packages cannot implement, the flexible programming tool R can handle, and that is where R really fits in. In other words, there would be few strong reasons for most of us to choose R over those standard packages.
     Academicians, researchers and students who are yet to go for their research projects, I encourage you to try R. If you have heard about it once or twice before but you are wondering what it is anyway you will not regret the results.
    God bless you all. See you on top.

The writer is a lecturer in Faculty of Science and Technology

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