RStudio Review
January 31, 2019

RStudio Review

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with RStudio

Rstudio has been used by most students who are in statistical classes dealing with data analysis. It has been installed in the statical computer labs for students to solve their class problems or conduct research studies including estimation of the time to failure of a structural/mechanical component, determining the probability of failure under certain conditions, and planning a reliability demonstration test, etc.

Pros

  • The data file can be imported from text files and multiple data files can be imported and processed in one R command window.
  • R commands and functions are embedded, so getting familiar with them would make coding in R easier.
  • The way of coding in R is not complex. If a beginner just started using R but has some background in other coding languages, it would help with coding in R as well.

Cons

  • Unlike other statistical software, RStudio does not display results at every coding step unless a command is made.
  • If your functions are not in the database of RStudio, users need to make their own by coding, which is not that easy to do for beginners with no previous experience.
  • RStudio helps to process data associated with the failure time of a mechanical component and evaluate the mean time to failure the probability of failure for this component.
  • Since there is no converter that can convert python or MATLAB languages to R, users need to rewrite the code or function in R.
  • RStudio is open source, so anyone can program RStudio and define their own functions.
Coding in RStudio is more convenient and plot display in RStudio can be more user-defined than JMP Pro.
RStudio is well suited for estimating the probability of failure since almost all of the probability distribution functions are available from the function database. For dealing with big data or machine learning algorithms, RStudio looks less efficient than other popular languages such as Python.

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