Hey everyone! I'm studying financial analysis and need to use a programming language for my thesis, specifically to run a panel regression with fixed effects. The issue is, I don't have much experience in data analytics beyond some basic statistics courses, and I've only worked with SPSS for simpler datasets. I've heard a lot about programming languages like Python, R, and Stata, but I'm unsure which one is the easiest to learn in the time I have available—just three months. Any suggestions on where to start or which language would be best for my situation? I'd really appreciate any help!
3 Answers
Honestly, you might be in for a tough ride if you want to jump into programming without any prior experience. It's like being an accountant without knowing how to use a calculator. If you're serious about delivering your thesis, you're going to have to learn quickly. SPSS is pretty outdated now, and while it’s still used, R seems to be the way to go. That said, R is also being replaced by newer options like Apache Spark, which works with Python—definitely the most popular choice now. If you're looking to make a solid start, I'd say go for Spark with Python, even if it has a bit of a learning curve. Just focus on learning enough to get your thesis done first!
Given your tight timeline of three months, I'd lean towards Stata. It's generally the easiest of the three for completing projects like yours, especially if you're not yet comfortable with programming. You might consider grabbing the book 'A Gentle Introduction to Stata' by Alan C. Cook—it’s really helpful and should guide you through your analysis nicely!
I’d suggest you try out R Studio. It's user-friendly and a lot of people say it’s the best starting point for data analytics. You might find you can get through your thesis without too much hassle!
I’ve heard R is a bit easier for beginners without programming backgrounds, though. My university taught SPSS too, which left me scrambling when I realized it wouldn't help for my thesis. I guess I’ll pick whatever's easiest first and move onto something more advanced later.