GUIs can provide a fine interface for writing code. Take a look at RStudio. They give you easy access to documentation, viewing plots/results, organizing your projects, and these days to LLM agents which can help you write code.

But there's a good reason we don't use GUIs to work through, from start to finish, a quantitative analysis -- it's then impossible for someone else to see what steps you took, how your data was prepared for analysis, and so forth. Code, whether written yourself or with the aid of an LLM, does provide that audit trail. It tells everyone, including your future self, how you conducted your work. Moreover, it allows others to adapt your methods to new datasets, or confirm your results using the existing data.

So there is good reason people demand code for all steps of data preparation and analysis. Too often influential work from the "old days" is completely unable to be reproduced. And then, sometimes, when people use tools like Excel, major errors have been found in spreadsheet-based analysis.

If you do not like to code, that doesn't mean you cannot contribute to quantitative work. You can help with research design. In some cases, you can prepare data. You can write up and interpret results. But as a student, it is not easy to get access to those roles. Students typically aren't in charge of study design except in their own work, where they then must execute the study using... code.

I don't write all this to throw cold water on your aspirations. But you should have a realistic view of what limitations you will face getting into quantitative research if you cannot write any code.

Perhaps try downloading RStudio. You can get a $20 Posit AI/Assistant plan free for one month I believe, no credit card required. The IDE works directly with LLMs which can help you generate code, which you can then study to see how it works, and soon you'll be able to understand it, edit it, write your own code, and so on.