JASP and jamovi are good. Here's where they stop.

Both are free, open source, well-built and backed by people who care about doing statistics properly. If you have not tried them, do. This page is not an argument against either.

It is about the point in your week where the statistics are finished and you still do not have a figure you can submit.

What JASP and jamovi are good at

• Free and open source, with no licence to expire.
• Genuinely excellent Bayesian analysis in JASP, better than most paid tools.
• Clean, teachable interfaces that update results live as you change options.
• APA-formatted output tables you can lift straight into a manuscript.
• Actively developed by academic teams with no commercial pressure.

Where Plotara differs

Publication figures rather than analysis plots. The charts in JASP and jamovi are built to help you understand your data, and they do that well. Plotara is built to produce the file you upload to the journal: 22 graph types, 15 journal styles, multi-panel layout at 90 mm and 180 mm, 300 DPI, SVG and PDF.

Specialist plots. Kaplan-Meier with at-risk tables, forest plots with OR, RR, HR, MD and SMD, dose-response curves with EC50 and IC50, clustered correlation heatmaps with non-significant cells masked.

Python export. Every analysis and figure comes with runnable Python.

Batch mode. Run the same analysis across groups, columns or sheets in one pass.

Side by side

Who should pick which

Use JASP or jamovi if you need Bayesian analysis, if cost is the deciding factor, or if you are teaching and need something every student can install for free.

Try Plotara if the statistics are already fine and it is the figure holding you up, or if you need survival curves, forest plots or dose-response fits.

Plenty of people use both. Nothing stops you running the analysis in JASP and building the figure in Plotara.