Free statistics software for Macintosh computers (Macs)
Updated 11/4/2024
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Free SPSS competitors—the do-it-all software
JASP, Jamovi, and PSPP are the free Swiss Army knives of Mac statistics software. They are all faster than SPSS, and import and export SPSS data and syntax files.
PSPP was first but development has been slowest. JASP was forked from Jamovi, but both are still under active development. They are interfaces for the hard-to-learn-and-use R, which has been quite well tested. All four of these programs (including SPSS) should provide similar numbers.
PSPP is the most like a SPSS used to be, but is awkward in many ways, with many bugs on the Mac; it’s good in Linux. JASP and Jamovi have a cleaner, newer interface, but they have diffrent features. PSPP is good for fast independent-samples t-tests, while JASP and Jamovi both make you take another step if the variances of the two groups are different; they are somewhat weaker in recoding and computing, so it’s best to prepare information for them somewhere else. Applying value or variable labels to JASP or Jamovi can be painful at best—they have to be done one variable at a time—but they can import them.
| JASP and Jamovi | PSPP | |
|---|---|---|
| Signed | Yes | No (can build yourself) |
| Statistics engine | R | Native |
| Output | Copies as tables | Copies as plain text |
| More modules? | Yes | No |
| Program windows | One | 2-3 windows |
| Syntax | R code | SPSS syntax |
| Contextual help | Yes | No |
| Command logs | Yes (can’t easily replay) | In theory |
| Mac open/save boxes | No | No |
| Download size | Jamovi 415 MB JASP 1.2GB! |
Small (~124 MB) |
| Cloud version | Yes | No |
| Speed | Lightning-fast | Lightning-fast |
JASP and Jamovi are easy to install; Jamovi allows plugins and JASP will later. Their interface has an Office 365-style open/save/print/export tab; options on the left, output on the right layout; instant changes to the output if you change the input; and export of both data and output, as desired.
Quick video comparing JASP and Jamovi...
The current JASP makes recoding easier than it was in the video, which we plan to update. Missing value handling is also much better, and it now imports from SPSS .sav data files.
PSPP does a fine job of cloning ancient SPSS but has some nasty bugs and quirks; on the other hand its journaling and syntax are very nicely done. Not having a real Mac user interface makes PSPP painful at times, but it’s probably the best of the bunch for Linux users. When considering each of these for my class, these are the pluses and minuses (this table really is best on a desktop, sorry!) —
| Program | Unique Goodness | Deal Killers |
|---|---|---|
| JASP |
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| Jamovi |
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| PSPP |
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| SPSS |
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The SPSS competitors in more detail
All three of the potential SPSS replacements have some oddities, as shown in the table above, which may not be addressed in the foreseeable future; the developers are adding a great deal of statistical capability without addressing these issues. One major addition is stepwise, forward, and backward regression added at last to JASP.
PSPP: The SPSS Clone
Listing updated 4/24/2024
Last known software update: March 21, 2024 (including Mac binary)
Download size: quite small! Unsigned software; source available
PSPP is a free SPSS clone with a Mac version you can download from this site (it’s unsigned). You can also build from source, but that's another level of effort (and, with MacPorts, a crazy amount of overhead to build one program). The pre-compiled Mac version is under 60 MB, and loads quickly, making SPSS look like a sloth. This would be my favorite SPSS clone, if not for a number of problems—the largest one being excess Mac and Windows bugs. Its ideal environment is Linux. Development is slow and doesn’t usually address any of these bugs. Here’s a video on installing it.
The interface is similar to SPSS, with menus in the windows rather than the menubar, and a frustrating version of the open/save box. It can’t use custom folders (including OneDrive and Dropbox). PSPP does import SPSS data files, long variable names, and variable and value labels. Common options are included in some dialogue boxes without the need to dig deeper.
You can copy from the output window—but only from the left-hand contents, not from the main pane. The output window yields plain-text, delimited by spaces and pipes. There’s also no way to clear anything from the output window.
Regression does not allow for multiple step entry or forward, backward, or stepwise models.
Our getting-started guide for SPSS is also helpful for getting started with PSPP.
The capabilities are impressive, including graphing. It’s a fine way to avoid spending thousands of dollars on the big cheese. A great deal of work has gone into the analyses themselves, and the routines the program does run are well fleshed out. The user interface is awkward, but it’s fast; while on SPSS it takes a long time for windows to form and disappear.
Version 2 boasts ctables, layered frequencies via split file, new aggregation functions, more symmetric-measures crosstabs, display macros, and show environment support. When adding, matching, or updating files, string variables with the same name can have different widths. pspp-dump-sav and modify vars have been removed; and GIMP has been replaced by the smaller rsvg-convert from librsvg2. It builds easily from source via Homebrew (to upgrade Brew installations, try just brew upgrade from terminal; it should upgrade everything on your consent, including PSPP); it is also available as a MacPorts formula.
Downsides.
- PSPP can't find .sav files unless you specify “all files.”
- PSPP only has a single-stage Enter for regression, making it quite clunky. There is no stepwise, forward, or staged Enter.
- Recent Files only works now and then and only if you specify “all files.”
- Some commands are not available in abbreviated form.
Until SPSS wised up, you could use PSPP to open SPV files with the original formatting. This stopped working with SPSS 28 (more so with 29). Even SPSS 28 can’t read many SPSS 29 output files! There is no SmartViewer for Mac past version 24, so you can’t read these files with SmartViewer either. Other than annoying stats faculty, it’s hard to see why these changes were made, but it’s yet another good reason to ditch SPSS itself.
JASP: the first really good effort at making R more accessible
Listing updated: 9/13/2024; program updated mid-2024
Not signed by Apple; but has an online version
1.2 GB download, a stunning 2.4GB on disk!
JASP was created as “a low fat alternative to SPSS, a delicious alternative to R,” by people at the University of Amsterdam. You can run it “in the cloud” — in your browser — for free. It’s not quite low-fat on disk, taking up 2.4 gigabytes of space.
JASP uses its own open/save dialogue box until you click Browse to get to the Mac-standards one. It has extensive Bayesian statistics capabilities which may confuse people who are not looking for them.
JASP supports value and variable labels alike.
The software looks and feels like SPSS to a degree; it feels as native as SPSS. Calculations and screen drawing are far, far, far faster than in “real SPSS” — when you select the tests, they might actually be pumped out before your finger is fully off the mouse. Stepwise regression is now supported. When you do t-tests, if equal variances are not present, it only prints out a warning, and you must switch to Welch’s t-test instead of using the dual-variances formula of the classic Student’s t-test (you can specifiy printing both); it does not apply Welch’s t-test automatically, nor is printing descriptives the default. The format for multiple t-tests is quite neat.
We loaded our large test file instantly, and ran descriptives instantly. Survey researchers will be happy to know they can assign value labels — and unhappy to know they must be done variable by variable, without syntax. Labels are retroactively applied to the output window. Variable labels are now supported on import as “long names,” but they don’t show up that way on output; for that matter, JASP doesn’t show the value lables. On the lighter side, computing new variables is relatively easy now.
t-tests require two-value group variables—you can't pick, say, Dodge vs Chrysler from a list of automotive brands; you have to create a new variable consisting solely of Dodge and Chrysler, which is a nuisance. Variable lists work in alphabetical order and don't show labels, so variable names have to be chosen carefully.
JASP is under rapid development. The speed is quite good. You can set the resolution of charts, so you can copy them at 300 dpi if you want.
JASP’s advantage over Jamovi is that it supports forward, backward, and stepwise regression, while Jamovi only supports "Enter;” JASP has niftier menus and nicer output; an integrated R syntax plugin; and Bayesian statistics up the wazoo. Jamovi does have its own advantages...see below.
There is a great deal of documentation in the newish book Learning Statistics with JASP. There is also a Machine Learning module.
In our run-throughs, the numbers were identical to SPSS, PSPP, and Jamovi.
Dive more deeply into JASP (full MacStats review).
Jamovi: deceptively powerful
Listing updated: 9/13/2024; updates are roughly once a month
See the an online “cloud” version
Signed by Apple
378MB download, 800MB in place
Jamovi: A free, open source package, built atop R (Thanks, Dr. Kim-Oliver Tietze). Jamovi uses a spreadsheet interface with full graphics, and allows both syntax and menus. You can edit via spreadsheet or internally; and your data, analyses, and options are saved in a single file, so others can reproduce your work. A large number of analyses are easy to find.
The results are attractive (see above), with menus that will be familiar to any SPSS users and with many options. Copying and pasting output is cleverly done; right-click on a section of output, and you can paste it into Word as a nicely formatted table. Paste into BBEdit, and it will be plain-text, formatted with spaces. There are three built in plot themes.
The online (cloud) version is also very responsive.
Syntax mode shows the R syntax for each menu command, helping you to learn it or to make scripts to reproduce the same actions over and over, ... except for importing data. Data can be imported in numerous ways, including SPSS, SAS, and Stata files. It supports variable labels but not value labels at all. In the past, not checked recently, export from Jamovi to SPSS resulted in errors on some data files as the number of characters in some fields was not correctly marked.
Shortcomings. Jamovi is very fast, but (like PSPP) doesn’t fully use the Mac interface; pretty much everything is instant, while on SPSS it takes a long time for windows to form and disappear. If you click on "Browse" in the file open/close menu, you get access to the native file selection system.
Jamovi’s menus are kept within its own window instead of at the top of the screen, and the open/save dialogue box is quite different, though it does show shortcuts for the documents, downloads, desktop, and home folders, and you can click Browse to get the standard interface.
Variable names have to be cleaned before importing data, because the variable lists work in alphabetical order and don't show labels.
For ideological reasons, you only get Enter for linear regression. You can however do multiple blocks which is at least better than PSPP if not up to JASP. Regression allows easy entry of factors and weights.
If you do a student’s t-test on groups with different variances, it prints a warning rather than using the alternate formula; at this point you must to switch to Welch’s test (it would be nice if descriptives were standard and if it switched automatically to Welch’s). t-tests require two-value variables (you can't pick, say, Dodge vs Chrysler from a list of automotive brands; you have to create a new variable consisting solely of Dodge and Chrysler), which is a nuisance, especially given the painful interface for recoding. This is the same as in JASP.
Other issues include no support for date or time variables; and no ability to direct output to new variables. You can’t copy and paste from BBedit into Jamovi, but must use its clunky though powerful data transformation system. The program is almost quite large on disk, due to the integrated software — R, Electron, Mantle, Python, and ReactiveCoca.
Other notes. Developer Jonathon Love pointed us to the Jamovi library of extra procedures. A long, well-illustrated Jamovi blog post also goes over the fine graphics capabilities within Jamovi, which PSPP can only dream of. In our run-throughs, the numbers were identical to SPSS, PSPP, and JASP.
Dive more deeply into Jamovi (full MacStats review).
Other free general statistics software
Past 4 (PAleontological STatistics): an absurdly wide-ranging, easy to use package
Listing updated: October 2024 (last software update, January 2024)
Signed by Apple (App store version)
“Past is free software for scientific data analysis, with functions for data manipulation, plotting, univariate and multivariate statistics, ecological analysis, time series and spatial analysis, morphometrics and stratigraphy.” That said, Dennis Helsel wrote, “While its name shows its origin (Paleontology), it is a full-fledged stat package which includes multivariate and permutation tests, with a nice interface.” There is good support for geographical and map-based statistics.
When Dennis says “full-fledged,” he isn’t kidding — the range of this software is stunning. Yet, the download is a mere 10 MB — far, far, far less than many others. What’s more, every new version brings a wide range of new features—even 0.0x versions. Summary statistics came in a fraction of a second on a laptop. Our survey file never caused more than a slight pause.
Downsides. Import formats are limited and exclude SPSS and Excel files; some rather esoteric formats are accepted, though, and you can copy and paste from Excel (with caution). Large files (e.g. 40,000 cases) can choke it. There are no value labels, but there are variable levels (click Column Attributes and you can enter variable names) and there is scripting.
You can transform data but without the flexibility of some other software; you cannot set missing values. Transformations tend to the complex, leaving out the simple. The "select data and then operate on it” format is clunky; and if you choose columns rather than specific data groups, the program essentially freezes trying to deal with a huge number of cases. There is no way to do independent-sample t-tests by having one variable define groups; you need to have each group in a different column, and only select the data you want to analyze.
Overall, Past is excellent for some of its features but people who don’t need its unique properties are better off with the others listed here.
Dive more deeply into PAST (full MacStats review).
SageMath
Listing updated: 10/25/2024 • Program updated 10/20/2024
Size: 3.5 GB (yes, GB)
SageMath is general math software, with the ability to do statistics. It can be used for just about any type of math, and can be used either with the command line or or from a web browser. You can install it onto a server if you want, and create embedded graphics, typset-style math expressions, and more; it also includes sharing. It is not a typical Mac program; it has a command line element and is accessed from browsers. SageMath was built atop NumPy, SciPy, matplotlib, Sympy, Maxima, GAP, FLINT, and R.
R (CRAN) / “R for Mac OS X” / R.App and R GUI
Geographic resources
- GRASS GIS is well supported, free open source software, and is frequently updated. Our last look was in November 2024. Michael Barton pointed out that GRASS is used for geographic resources data management, image processing, graphics production, spatial modelling, and visualization of many types of data. It was started by the Army for land management and environmental planning and is now used in many areas of research by academia, government, and businesses. Attributes are managed in a SQL-based DBMS. GRASS 6 added a new vector engine, vector network analysis, a new display manager, and many other changes. This is an extensive program.
- Quantum GIS is a less powerful but easy to use GIS package for Mac, Linux, and Windows with strong organizational support. It supports numerous vector, raster, and database formats and functions. Last viewed October 2024.
- Generic Mapping Tools, or GMT, is an open source collection of many tools for manipulating geographic and Cartesian data sets (including filtering, trend fitting, gridding, projecting, etc.) and producing illustrations from simple x-y plots via contour maps to artificially illuminated surfaces and 3-D perspective views. A MATLAB extension is available.
Also see
- Graphing and visualization software (including packages that do statistical routines, e.g. Aabel)
- Commercial software
- Dead software
- Gene Shackman’s site devoted to free statistics software
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