You mention that you are going to be scripting most of your work, and personally I find SPSS's scripting syntax absolutely horrendous, to the point that I've stopped working with SPSS whenever possible. I haven't found a robust solution for R to accomplish this same task. Labeling of data -> SPSS does a pretty good job with the variable labels and value labels. The equivalent function in R involves learning LaTex or using a odfWeave or Lyx or something of that nature. These can relatively easily be transported to Word Documents or Excel sheets for further analysis / presentation. Output of tables - SPSS has basic tables, general tables, custom tables, etc that are all output to that nifty data viewer or whatever they call it. Some of the biggest differences I have run into include: I work at a company that uses SPSS for the majority of our data analysis, and for a variety of reasons - I have started trying to use R for more and more of my own analysis. I will be mostly working with scripts in either case anyway so I wanted to know about the other differences. I am not asking which one is better, but just wanted to know what are the difference in terms of workflow between the two (besides the fact that SPSS has a GUI). Therefore, I was wondering what is the basic difference between these two softwares. I will also be generating quite a lot of graphs and charts. 
I have found that R and SPSS are among the most popular tools for statistical analysis.
I will be analysing vast amount of network traffic related data shortly, and will pre-process the data in order to analyse it. Are different, depending on your operating system either Microsoft. You can think of installing R as buying car and of installing R and RStudio as. This tutorial covers the installation of R on Microsoft Windows, Mac OS X.
0 kommentar(er)
