Any serious researcher will fight you to the death to convince you
that their favourite stats program is THE best stats program. But, there
are good and bad things about each of them.
SPSS: Great for people who rarely use statistics, who don’t remember code, who are scared by code, have no time to learn code, who just need to use some of the basic processes with no special adjustment, who work with normal data that never changes. It’s quick and easy to learn and use, and you don’t 4 feet of manuals to find what you’re looking for. You can just click through the menu to find all the basics you’ll ever need. Compared to SAS, SPSS is major el cheapo.
SAS: Great for people who love coding. SAS does have a menu version but if you like menus, then you should be using SPSS. SAS is great for data manipulation as in creating brand new variables, flipping cases into variables and vice versa, and re-running the same bit of code repeatedly with only a tiny change every time. The macros you can write are unlimited and awesome. And, if it doesn’t do the variation of a statistic you want, you can actually program that statistic into SAS. If you like collecting books, SAS can quickly contribute to that addiction. Buy them. You will need them.
R: What? A third choice? Oh yes. R is great for people who want to flaunt how anti-establishment they are. It’s open source and requires a lot of commitment to become competent. But it can do any statistic you’ve ever dreamed of and a billion more. And you can brag that you know hard core statistics programming. Do not attempt to learn it if Excel intimidates you. Otherwise, go and download it right now and get ready for a rip-roaring awesome 6 week holiday. It is free so prepare to salivate. Mmmmmm…. rrrrrrr. There are even a couple of self-help books now so you might want to find one of them. So, if you’re fresh out of school and no longer have the student version of SAS, R will be perfect for you.
What’s my preference? Well, I wish I was competent in R
SPSS: Great for people who rarely use statistics, who don’t remember code, who are scared by code, have no time to learn code, who just need to use some of the basic processes with no special adjustment, who work with normal data that never changes. It’s quick and easy to learn and use, and you don’t 4 feet of manuals to find what you’re looking for. You can just click through the menu to find all the basics you’ll ever need. Compared to SAS, SPSS is major el cheapo.
SAS: Great for people who love coding. SAS does have a menu version but if you like menus, then you should be using SPSS. SAS is great for data manipulation as in creating brand new variables, flipping cases into variables and vice versa, and re-running the same bit of code repeatedly with only a tiny change every time. The macros you can write are unlimited and awesome. And, if it doesn’t do the variation of a statistic you want, you can actually program that statistic into SAS. If you like collecting books, SAS can quickly contribute to that addiction. Buy them. You will need them.
R: What? A third choice? Oh yes. R is great for people who want to flaunt how anti-establishment they are. It’s open source and requires a lot of commitment to become competent. But it can do any statistic you’ve ever dreamed of and a billion more. And you can brag that you know hard core statistics programming. Do not attempt to learn it if Excel intimidates you. Otherwise, go and download it right now and get ready for a rip-roaring awesome 6 week holiday. It is free so prepare to salivate. Mmmmmm…. rrrrrrr. There are even a couple of self-help books now so you might want to find one of them. So, if you’re fresh out of school and no longer have the student version of SAS, R will be perfect for you.
What’s my preference? Well, I wish I was competent in R
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