Let’s talk about statistical software. Each one is helpful depending upon how it is used in your every day analysis. Excel is considered your low-end software package that comes with Microsoft Office . It’s easy to use and accessible to anyone. It’s a good data entry package. I would definitely use it for class calculations because it organizes your thoughts. You can copy and paste equations to make your work easier. You can graph illustrations with it. But I do not use it for statistical analysis. It’s not really popular for statistical analysis. People typically use more stronger packages. There is STATA which  does not require extensive programming to view the file. There are short-hand commands that generate a lot of statistical output in STATA. Personally, I think STATA is expensive for non-students. There are less expensive packages you could access on the web, such as,  R statistical software. R programming software is free. You can download it to your computer and generate any statistical analysis procedure. You must get use to upgrading your session  to access specific statistical applications. I do not particularly care for R but it’s a highly recognized statistics package and you want to stay up to date on the latest tools. SPSS is another package that people use in academia. It is easy to use and moderately priced  for students and non-students. It can export and read any file type. But you  can not see the data manipulation in real-time. SAS is good for showing the data file manipulation but you have to learn how to program in SAS language which might be a problem.

I would use SAS  for a thesis , dissertation, or publication because I can track changes to my data file and I am comfortable with it.  You should choose a program you are comfortable with in general. It’s not a good idea to choose something that you need to learn from scratch- especially at the thesis/dissertation phase. You want to focus your time on the research than anything else.

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