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WatermelonPig
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Especially in comparison to SAS? I really don't have the money to buy SAS and I can't get it from my school so I'm looking for alternatives.
R is widely used in both industry and labwork, particularly in fields such as data analysis, statistics, and machine learning. Many companies and research institutions use R as their primary programming language for data analysis and modeling.
Yes, R is considered a legitimate language for scientific research. It has a robust set of statistical and data analysis packages and is widely used in academia for scientific research in various fields.
R is generally slower than languages like Python or C++ due to its interpreted nature. However, with the use of efficient packages and techniques such as parallel processing, R can achieve comparable speeds to other languages for data analysis and modeling tasks.
One limitation of using R in industry and labwork is its lack of support for large, complex datasets. R is not as scalable as other programming languages, which can make it challenging to handle big data. Additionally, R may not be the best choice for tasks that require real-time processing or interaction with other software systems.
While a strong background in statistics can be helpful when using R, it is not a requirement. R has a vast and supportive community, and there are many online resources available for learning and using R for data analysis and modeling. Additionally, there are packages and functions in R that make statistical analysis more intuitive and accessible for those without a strong statistics background.