**ESCI** Geoff Cumming has developed ESCI (Explortory Software for Confidence Intervals). - esci is now a module in the jamovi library. This is the laterst iteraction of esci. It can currently do all the analyses included in older versions, but in a modern statistical environment. Instructions on installing are [here][1]. - the older version of ESCI is a set of Excel files. These provide simulations and analysis tools for understanding the New Statistics. - ESCI is provided free of charge. Download the latest version [here][2]. - ESCI has been updated several times. You can find a list of versions and updates [here][3]. **[Jamovi][4]** [Jamovi][5] is a free, open-source program for data analysis. It is built on R but provides a beautiful interface. Jamovi is also extensible--new modules can be developed and then posted to the Jamovi store. Right out of the box Jamovi does a pretty good job with providing estimation output. It is under active development with new features being released regularly. You can add the esci module into jamovi. Just click on "Modules", then browse the available modules to find and install esci. The github page for this ongoing project is: [https://github.com/rcalinjageman/EstimationStats][6] **[EstimationStats.com][7]** This web-based tool provides estimation graphs and summary data for a number of basic designs. The graphs are lovely and the source code (for Python) is available. Under actie development. **[JASP][8]** JASP is a free, open-source analysis program that is particularly focused on Bayesian analyses. It can provide credible intervals for the comparison between two means (paired or independent). It is under active development with new features being released regularly. **SPSS** SPSS does not do the best with the estimation approach. But it can do provide acceptable output for at least some designs. Bob Calin-Jageman has written a short guide to using SPSS with the estimation approach. You can download it [here][9]. Bob Calin-Jageman was also developing ESPSS, a set of SPSS extensions to provide estimation-style output. Only thee independent and paired t-tests were complete. This project has been abandoned, but you can download the latest versions from github: [https://github.com/rcalinjageman/ESPSS][10] **R** R makes pretty much everything possible, though not always easy. David Erceg-Hurn has written a very nice guide to using R for the estimation approach that covers the basics. You can download it [here][11]. **Meta-Analysis Tools** [Here][12] is a handy guide to a number of different software tools for meta-analysis. [1]: https://thenewstatistics.com/itns/esci/ [2]: http://thenewstatistics.com/itns/esci/esci-for-itns/ [3]: http://thenewstatistics.com/itns/esci/ [4]: https://www.jamovi.org/ [5]: https://www.jamovi.org/ [6]: https://github.com/rcalinjageman/EstimationStats [7]: http://www.estimationstats.com [8]: https://jasp-stats.org/ [9]: https://osf.io/736n6/ [10]: https://github.com/rcalinjageman/ESPSS [11]: https://osf.io/rmn8p/ [12 [10]: https://osf.io/rmn8p/ [11]: https://osf.io/jx2td/wiki/Meta-Analysis%20Tools/