Posit Description
At Posit, we strive to enhance data science by making it more open, user-friendly, accessible, and collaborative for everyone. Our suite of tools empowers individuals, teams, and enterprises to utilize advanced analytics to derive meaningful insights and create a significant impact. From our inception, we have committed to open-source software, such as RStudio IDE, Shiny, and tidyverse, because we firmly believe in democratizing access to data science tools. We offer R and Python-based solutions designed to streamline the analysis process, enabling you to achieve higher-quality results in less time. Our platform facilitates secure sharing of data-science applications across your organization, reinforcing the idea that our code belongs to you. You can build upon it, share it, and use it to enhance the lives of others. By simplifying the processes of uploading, storing, accessing, and distributing your work, we aim to make your experience seamless. We are always excited to learn about the incredible projects being developed using our tools globally, and we cherish the opportunity to share those inspiring stories with the community. Ultimately, our mission is to foster a vibrant ecosystem where data science can flourish for everyone involved.
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Statistics and graphs Date: Mar 23 2022
Summary: I've been studying statistics for the last year and RStudio is the easy part. You get a lot of value by visualising stuff and it's easy. It automatically calculates correlations, associations, confidence intervals, prediction intervals, p/t/f values... Even if you just have a straight list of numbers you can get a boxplot, standard deviation, test normality...
Positive: Powerful statistical tools.
Good quality customisable plots, all different types using all different data and models.
Easy to import from csv and there's plenty of datasets around if you go looking.
Easy to create and export graphs.
Being able to quickly and easily visualise (and share) data is more useful than I could have imagined. All the "academic" data online is suddenly easy to use.
I haven't even scratched the surface of community created packages, but they're easy to install, not always so easy to use.Negative: You can get unhelpful syntax error messages.
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The basics work well but sometimes just changing something (eg colours) in specialised plots feels like a hard programming puzzle.
It's mostly straight-forward like "plot(data)", but the commands are written in a programming language and get tricky depending on your needs.
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