# Advantages and disadvantages of statistical software

I saw lots of questions regarding choice of statistical software for data analysis. I want to choose some statistical software for data analysis.

We could use more than one statistical software for our purpose. When we look at common statistical software, we see three or four main programs. These are SAS, Mathlab, Statistica and R. Maybe Minitab and SPSS could be added to them. Some of them need high profiencies because they work via coding language. The non-code programs such as SPSS, have disadvantages because of their graphical results not improving and model intervention is limited. For this reason, using the program working with code such as SAS, R, Mathlab is very efficient for scientific studies. R is free statistical software and it has many options about data analysis. It is promoted by not only statistical packages but also other packages such as psychological and social approaches. I prefer the interpretion of my results via multivariate graphical methods which have cases and variables could be shown in the same graph (such as Cannonical Discriminant HEPlot, Principal Component Biplot etc.). These methods need heavy program codes but they are very effective for interpretion of our results. SAS is another choice but it is not free. Both of these software are strengthened and differentiated from other choices via packages and macros.

We could use more than one statistical software for our purpose. When we look at common statistical software, we see three or four main programs. These are SAS, Mathlab, Statistica and R. Maybe Minitab and SPSS could be added to them. Some of them need high profiencies because they work via coding language. The non-code programs such as SPSS, have disadvantages because of their graphical results not improving and model intervention is limited. For this reason, using the program working with code such as SAS, R, Mathlab is very efficient for scientific studies. R is free statistical software and it has many options about data analysis. It is promoted by not only statistical packages but also other packages such as psychological and social approaches. I prefer the interpretion of my results via multivariate graphical methods which have cases and variables could be shown in the same graph (such as Cannonical Discriminant HEPlot, Principal Component Biplot etc.). These methods need heavy program codes but they are very effective for interpretion of our results. SAS is another choice but it is not free. Both of these software are strengthened and differentiated from other choices via packages and macros.

## All Answers (7)

Shazia HarisJoseph Tkacz· Health AnalyticsCraig Smeaton· University of St AndrewsMohammad Tahir· Sugar Crops Research Institute MardanMatthis Drolet· German Primate Center1) The learning curve is less semantic (as with other scripting languages) than conceptual. And learning the concepts involved in R can actually give you a much deeper understanding of statistics than most point and click stats programs can (yes, some offer both, but if you are going to learn scripting stats, I would still recommend R for the other reasons above).

2) I highly recommend Rstudio to get you started. It gets a lot of the hassle of learning R out of the way at the beginning and there are enough tutorials on learning R online with Rstudio now, which makes it even easier. And it is the one GUI that I find really works for R without taking away the stats scripting that makes R so powerful.

http://www.rstudio.com/

ps. no, I am neither an R or Rstudio developer, just a happy user ;)

Fatih Kahrıman· Çanakkale Onsekiz Mart ÜniversitesiI agree with you about advantages of R. First of all it is free and than it is very innovative. I am neither statistician nor R developer too. But I see clearly that R offers many approches for special options researchers like me. Except of SAS and Mathlab, other programs could not solve the problems about special subjects. I think so that package developers are also employees about special subjects. So if you study about a special research area you could clearly understand the value of software with command syntax language such as R and SAS.

The last word as says the crowd "Best choice for you, ones who makes you want to."

Best wishes

Khaled F M Salem· Minoufiya Universitythe advantage of software is easy for analysis. The disadvantage is that you must know the right way for analysis otherwise the program analysis your data but with wrong status

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