<aside> 📢 All statistical software are essentially fancy calculators. They are tools that help us explore data. At the end of the day, I don't care which tool you use so long as you are creating code/syntax/procedures that are sharable and reproducible.
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<aside> 🤬 Big learning curve. So many benefits. Can do pretty much anything if you put in the time to learn how. R code is easily shared with others and fosters solid open-science practices. I am still learning, but have found it to be a rewarding process.
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<aside> 🤖 More user friendly. Great, free alternative to SPSS. Allows you to save analyses as R code for sharing. I use it all the time for quick analyses and initial data visualization.
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<aside> 🧐 Very similar to Jamovi with different statistical analysis modules. Allows you to save analyses for sharing. However, it does not allow for saving R code like Jamovi.
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<aside> 😱 More user friendly than R, but with some downsides too.
- It is expensive, thus prohibiting many from reproducing your analyses even if you share the syntax.
- Limited capabilities. SPSS can do many standard statistical analyses, but it often lags behind current trends.
- It creates UGLY plots and figures. Fine for exploring data, not so great for showcasing it.
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