From achieving a 42% and 50% in my undergraduate Data Analysis modules, I never thought I would be saying this - SPSS statistics is a life saver. You may be sat reading this think I must be mad, SPSS is the most confusing software ever, and you dreaded every data analysis computer lab at university. But what if I told you SPSS is not all doom and gloom. Despite my lackluster undergraduate data-analysis results, I actually managed to turn this around in my masters Quantitative Stats module, receiving 83% (which ended up being my highest module mark that year! Who would have thought??).
SPSS, once you get the hang of it, is incredibly easy to understand. Upload your data, choose what test you want to do, push a few buttons, and BAM, results. The challenge (in my opinion), is learning to read the tables and picking out the specific data you need to write up your analysis. This varies with each individual test on the programme. However, there are countless numbers of youtube tutorials and website pages to guide you.
Anyway, I'll get straight to what has driven me to write this post. R Statistics, R Studio, what ever you want to call it. Saying the very name gives me pain. I've been encouraged (against my will) by my PhD supervisor to use R to analyse the data for my systematic review. At the beginning I was very open to the idea - to increase my skill set, learn some new things, learn to use code etc. I've quickly come to realise that coding is not my forte. I have found it vastly more confusing than I ever thought SPSS to be, requiring much more patience, which if you know me, I do not have a lot of. And because of this, I have come to appreciate the existence of SPSS a lot more.
Just to clarify, I have managed to sort out the code required for my meta-analysis, but not without a week's worth of confusion and ultimately asking a fellow PhD student to share their code with me. Once you have to code you need to use for your specific test, it is fairly simple to input the commands you want into this and press 'ENTER'. But obtaining this information was a challenge. I turned to youtube, and there were multiple videos with extremely different methods and code, different ways of uploading data which didn't make sense to me, and different packages they were using. I'm just glad for my fellow PhD student who had managed to crack the code beforehand.
So, what have I learned from this experience?
- Mastering statistics programmes takes TIME! And a significant amount of it.
- Having a good teacher makes all the difference. My statistics lecturer for my masters degree was such an amazing teacher I actually emailed him to notify him of this fact.
- Not understanding one programme is not the be all and end all - there are so many out there (not all fully available without a subscription though).
- Don't be afraid to ask, even if you find yourself asking the same questions multiple times - it may just take this much to finally get your head around it.
- SPSS is the GOAT.
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