Hi.

If I want to pursue research in business on PhD level, that is going to be both qualitative and quantitative, what is better to do:

- Learn to use SPSS?
- Learn to write R code?

Thanks.

Depends on:
- What kind of analysis you intend to do (e.g. if the quantitative analysis doesn't go beyond logistic/linear regression then SPSS may suffice).
- What you might want to do after the PhD
- Your current level of skill/confidence.

SPSS is easier to use (so I gather) whereas R is quite challenging (which I think you're probably aware of given your post). R is becoming more an more popular in a variety of areas, particularly given that it's free.

This is worth a read if you want to get a feel for the challenges of learning R if you've used a commercial package in the past:

Have you thought about Stata? I think it's better than SPSS for most statistical analysis but not as tough to get to grips with than R (and handles large datasets better than R if that's an issue). That said Hazyjane's right - if you only want to do basic regressions then SPSS is probably fine and possibly the easiest, although I loathe it personally. It's just that if you want to do anything more interesting that SPSS becomes cumbersome and limiting.

FWIW I am also a Stata user. I'd agree with bewildered's comments. I don't know if there are many Stata users in the business world but I think it's quite popular with economics researchers.

Thank you all for you feedback.

I think that SPSS will do it. The data I will collect won't be massive. I've some basic knowledge of SPSS, whereas no knowledge whatsoever about R. And I think if SPSS isn't enough, I will consider Stata.

Thanks again.

Sounds sensible. Just one more thing before you commit yourself. Check what program the people most likely to be able to help you use. If they're all Stata users it might be better to go for that from the outset!

Good advice. Makes sense to me. Thanks a lot.

I would also check what training is available to you at your University - e.g. at mine the grad school training is focussed mainly on SPSS and Nvivo so it would make sense to use those packages as there is support available. So yes as others have said, see what your collegues use, see what software you can get free or reduced price as a student/staff member at that university.. and also consider what analysis you wish to do. I used a mixture of Excel, SPSS and M+ in my purely quantitative PhD. SPSS does far more than just 'basic regressions' as other posters have mentioned..there are a number of add ons you can get for SPSS to do more more complex analysis too, good luck!

Also thanks to you psychresearcher.

As I can say now based on all responses, it has to do more with what my institution has available and provides support for, and of course what kind of research I'm doing.

Since I'm not yet accepted in any institution, I thought it would be wise in the preparation process for my research career to have enough skills in a specific statistical package/ programming language, and wanted to see what would be best to start with.

I feel closer to SPSS, since I've said, I've used it before. However I saw a huge community talking about R. Also STATA and SAS are very popular out there, so I had to consider my options.

I've to choose something at the beginning. At some level all the packages will have the same functionality. Therefore for starters SPSS. After elaborating my skills in SPSS, I will try to get familiar with STATA. I will also look into Nviva since it is strong in qualitative research.

If my institution uses SPSS, then all is fine. If it is STATA / Nviva, then I will have a head start. And if none of these, then I can't do anything. I will have to learn it. It is unlikely for someone to be proficient in all statistical packages.

Many thanks to all. I'm feeling the benefit of these forums.