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Carrying out statistical analyses by hand can only take you so far. Usually, we need computers to help us manage large amounts of data. One software program that is used by a lot of people is SPSS. There are many other programs you could use to manage data, such as STATA, R, SAS, or even Excel. I tend to use STATA when doing my own research because it is more powerful and I find it easier to use with syntax and for my purposes. SPSS is often recommended for people just starting out because of it is seen as easier to use. You can argue with me about it, I don’t have strong feelings about which one is better, except that I have only used R once and I haven’t used SAS in a long time, so I prefer sharing what I know. Since the textbook I’m currently teaching Applied Statistics from discusses only SPSS, I’m going with that here. If I were to summarize the pros and cons, off the top of my head, I’d say:

1. Relatively easy to use
2. Used in many workplaces/schools, so it might be provided by your employer/school
3. Will do everything you need to do as a beginner
4. Very user friendly for the visual learner

1. Stupidly expensive and requires a license, so you can’t just buy it and own it. (Note: R is free and SAS and STATA don’t require that the license be renewed annually (at least SAS didn’t the last time I used it).
2. I believe that there are certain things it cannot do, or is not as fast or good at, such as multi-level analyses or structural equation modeling; but it’s been a while since I tried to do those and I found other solutions to those (Stata and MPlus, respectively).
3. If you get really good, harder to program it to do whatever you want (R and SAS are probably the best for this, with STATA a close third)
3. Doesn’t allow you to flex on other data analysts b/c it’s kind of like the tricycle of software programs… but a tricycle that works just fine.