I'm a statistician with more of a theoretical background than programming skills, and I'm curious if Haskell is a capable option for my field. I'm looking for statically typed programming languages that prioritize computations over app development. I want to move away from dynamic languages like Python and Julia since they tend to overwhelm me. When I work with dynamic languages, I often feel like I lose focus on the math since I find myself relying on built-in functions like mean(row1) instead of coding the mean function myself. Can anyone suggest a solid statically typed programming language suitable for master's or PhD work in statistics and mathematics?
4 Answers
To be honest, there aren't many statically typed languages that are widely used for statistics. Most of the popular stats packages, like R and Python, are dynamically typed for a reason—they simplify data analysis. R excels in this realm due to its extensive modeling and graphic capabilities. If you're focused solely on statistical coding, you might explore Scala, but be warned that it has a steep learning curve and a hefty abstraction layer. If you want to dig into numerical methods, looking at how R and Python interact with lower-level languages like C or Fortran could be beneficial. Really, if you’re applying statistics, I’d stick with R or Python, as it’s not laziness; it’s just more practical than reinventing the wheel with custom functions. You're better off focusing on your theoretical work rather than creating everything from scratch!
Thanks for the input! I do want to stay efficient and not get bogged down by coding everything myself.
Honestly, for what you want to do, R simplified a lot of complex tasks. Give it another shot if you can!
I appreciate the reminder! I’ll consider revisiting R.
Stick to R, MATLAB, or Mathematica if you want something powerful but manageable for statistics. If you want to challenge yourself, Fortran or C are tough choices, but can be rewarding if you’re up for it!
Thanks! I might just stick with R to avoid overwhelming myself.
I work in research with Rust, and it might fit your needs if you're open to it. It's statically typed but still has libraries for data manipulation. Haskell is interesting but lacks a robust ecosystem for practical data analysis. If you're inclined to try something unique, consider OCaml or F#. They have strong communities for data science, but if you want something more traditional, R or MATLAB are your best bets. Fortran and C are options, but I wouldn’t recommend them for statistics due to their dated nature. You might find yourself longing for the conveniences of a dynamic language!
Thanks, I’ve been assessing Rust lately! Might give it a shot.
That's helpful to know! I’ll definitely explore Rust a bit more.
Appreciate the suggestion! I guess I need to be realistic about what tools can help streamline the process.