Advantages and disadvantages of statistical software
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.