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Current Version: 1.01
Listing updated 4/4/2018
Like SPSS, PSPP is aimed at social scientists, business people, and students, with a convenient, easy to learn interface. The installation trouble makes me reluctantly suggest you look elsewhere, unless you run Linux.
The interface is similar to SPSS, though there are some oddities from the Linux background (including, like SPSS itself, putting menus into the windows and not in the menubar). It imports SPSS data files, long variable names, and variable and value labels. PSPP is much faster than SPSS itself; common options are included in some dialogue boxes without the need to dig deeper, another improvement over the original. Development seemed to accelerate in the last year or two.
On the down side, there are fewer tests and functions, as you’d expect. Also, while you can copy from the output window, you have to copy whole groups at a time (from the left-hand list, not from the main pane), and the output window copies plain-text, delimited by spaces and pipes, just as SPSS 4 did. That’s not ideal for importing to spreadsheets or word processors, unless you’re really, really good at using BBEdit’s GREP and macro features. There’s also no way to clear anything from the output window; you have to use control keys instead of command keys; the “recent files” feature doesn’t work; an error message comes up when you quit. Oh, and ... don’t try to compile from source.
However, the capabilities are impressive, including (but not limited to) graphing, data transformation, crosstabs, tables, various t-tests, ANOVA, regressions, factor analysis, ROC curves, and nonparametric tests.
Current Version: 3.17 / requires OS 10.8-10.11
Listing updated: 11/2017 (program updated November 2017)
Not signed by Apple (you may see a warning)
“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.”
When Dennis says “full-fledged,” he isn’t kidding — the range of this software is stunning.
Our test file imported in less than a second. Summary statistics came in a fraction of a second on a laptop. Linear correlations were instant; Kendall’s tau took a while. If you use a really, really large file, it can choke the software, because it doesn’t seem to take advantage of multiple processors, and there’s no apparent way to stop an ongoing process, so save often if you have a massive amount of data. Our survey file never caused more than a slight pause.
Current Version: 0.8x (Mac, Windows, or Linux)
Listing updated: 4/2018; program updated 4/2018
Cryptographically signed by Apple
Jamovi: A free, open source package, built on top of an R foundation (Thanks, Dr. Kim-Oliver Tietze). Don’t let that put you off: Jamovi uses a simple spreadsheet interface with full graphics, and while it allows you to use syntax, you can also use menus. You can edit via spreadsheet; 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, or you can use R syntax.
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. Plots can also be copied and pasted, but seem to be limited to screen resolution; there are three built in plot themes, including an SPSS-clone one.
A syntax mode shows the generated R syntax for each menu command, helping you to learn R syntax or make scripts to reproduce the same actions over and over, ... except for importing data. Data can be imported in numerous ways, including formatted SPSS files and, according to the programmers, SAS and Stata files. When we imported an SPSS file, variable labels came through, but not value labels.
Jamovi is fairly fast, but doesn’t fully use the Mac interface (for example, its menus are kept within its own window instead of at the top of the screen; more annoyingly, the open/save dialogue box is very different, though it does show shortcuts for the documents, downloads, desktop, and home folders.) You can, however, drag and drop data files onto it — saving time.
Developer Jonathon Love pointed us to the Jamovi library of extra procedures.
The program is almost 700 megabytes in size, due largely to the integrated software — R, Electron, Mantle, Python, and ReactiveCoca. We haven’t yet run it with our large sample dataset to compare results with other software, but since it’s based on R, it should be accurate and in line with other packages.
Current Version: 0.8x (requires OS 10.11+)
Listing updated: 4/2018; program updated 2/2018
Not signed by Apple (you may see a warning)
JASP was created as “a low fat alternative to SPSS, a delicious alternative to R,” and comes out of the University of Amsterdam (presumably at lower cost than buying SPSS).
JASP is not yet at version 1 and may be used with caution; it also requires the free XQuartz window environment. It does use the native open/save dialogue box, surprisingly; and it’s easy to install, unlike, say, PSPP.
The software looks and feels like SPSS; though it isn’t native Mac software, it feels more native than some of SPSS’ past versions. 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.
We loaded our 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. The labels are retroactively applied to whatever is in the output window, very rapidly.
Configurations Available: Intel processors (10.6+)
Current Version: 5.05/1
Listing updated: 4-25-18
MacAnova is a free, noncommercial, interactive statistical analysis program developed by Gary Oehlert and Christopher Bingham of the University of Minnesota School of Statistics. Their web site notes:
MacAnova has many capabilities but its strengths are analysis of variance and related models, matrix algebra, time series analysis (time and frequency domain), and (to a lesser extent) uni- and multi-variate exploratory statistics. MacAnova has a functional/command oriented interface. The Macintosh and Windows versions also have several window/menu/mouse type features. Although the language and syntax are S-like, MacAnova is not S or R.
MacAnova is now Intel native, and there is source code available. We found the program started up very quickly on a Intel Mini and had a fairly good menu system, which output visible code that we could copy and manipulate, or save and run later. It is almost similar to SPSS 4 in that regard, though better integrated into the system and lacking a separate output window. This is certainly worth a download. MacANOVA includes linear model and GLM routines.
Current Version: 2.7.4 (updated May 2017)
Listing updated: April 2018
Michael McLaughlin’s Regress+ is a free package that includes regression, stochastic modeling, bootstrapping and robust goodness of fit measures. The software and a tutorial are available at the Regress+ web site. Older versions are still available for older operation systems, while version 2.5 is available for OS X and 9.2.
Regress+ 2.7, née Regress+ 3.0, is a complete rewrite; it adds data modeling (equations and distributions), extensive documentation, and publication quality graphics.
This program appears to cover every aspect of regression you can think of. It's graphically oriented but has strong statistics. The code is “more than 100 times faster than before.”
Version 1.46; Listing updated April 2018; Source code updated 11/2017
SOFA Statistics (Statistics Open For All) is a graphical-interface statistical package with an emphasis on ease of use, discoverability, and clean reporting. It can connect directly to several database sources, or can use data brought in from spreadsheets. The usual statistical suspects are available, including one-way ANOVA, t-tests, signed ranks, chi-square, and R; nested tables can be produced with row and column percentages, totals, sd, mean, median, and sum.
SOFA Statistics is written in Python, using a wxPython widget toolkit. Statistics come via the Scipy stats module. Analysis and reporting can be automated using Python scripts, either exported from SOFA or written by hand.
Configurations: Mac and Windows
Listing updated: 1/2017; software updated 2006 or 2011
Not signed by Apple (you may see a warning)
Gary Smith’s Smith’s Statistical Package (SSP) is free and user-friendly; sadly, it seems to have ended development six years ago. It’s too old to have been signed by Apple, so to install it, you need to right-click (or control-click) the program icon and say Open, then fill out the scary dialogue box. We ran descriptives on our big test file instantly, including a histogram; but we could not copy the text anywhere else. Indeed, all the tests we ran were literally instant, but you have to copy down the numbers yourself — no outputs are copyable. The software is usable and fast, but you can probably do better; the number of tests are fairly restricted and sometimes the easy user interface gets in the way. It should be good for exploration and student use.
Configurations: Java; should work on Intel and PPC Macs
Current Version: 4.3
Listing updated: 1/2017
Statistics101 is giftware to help teach probability and statistics the easy way—by simulation. “Gain deeper understanding of traditional statistics concepts and methods. Increase your awareness of the role of variability in probability and statistics. Learn and apply simple to very sophisticated statistical techniques without tables or complicated formulas.” Interprets and executes the simple “Resampling Stats” programming language. The original Resampling Stats language and computer program were developed by Dr. Julian Simon and Peter Bruce to teach statistics.
Python software / Listing updated: 4/24/2018 / Software updated 2014
Salstat dates back to the early 2000s and runs on Python; installing the free version on the Mac may require quite a bit of library-and-Python downloading, but a paid version makes everything easy. There is a reward to the work of installation, though, in a free program which makes highly presentable graphics, is relatively easy to use, provides a great deal of descriptive statistics with parametric and nonparametric tests, shows its own source code, does crosstabs, and “charts, imports CSV, HTML, XML, Excel, LibreOffice and SAS file formats, and can even scrape tables of data from web pages.” The source code listing claims a last-update date of 2014.
Configurations Available: PowerPC (thru 1.7); Universal Binary (2.3+); Linux
Current Version: 3; under active development
Listing updated 5/2013
This is an exceedingly flexible program, with a large number of libraries and built in routines, and the ability to run many S or S-Plus programs. R loads and runs quickly but has a steep learning curve.
R programs and algorithms are distributed by the Comprehensive R Archive Network (CRAN). A simple and somewhat frustrating graphic user interface is included for Mac users; R Commander can be installed using the built-in package installer, which can also install file import features (which aren't installed by default). R Commander is an X11 program, which means it uses an alien interface and has odd open/save dialogues, but if you get past that it offers menu driven commands not dissimilar from, say, SPSS, just a lot more awkward to use, and without an output or data window.
There are now numerous front ends for R, several of which are mentioned earlier on this page.
R has a massive range of tests, PDF and PostScript output, a function to expand zip archives, and numerous other unexpected features. For much more information about R, including advantages, drawbacks, resources, and tips, see our incredibly outdated R statistics software for the Mac page.
Current Version: 1.1x
Listing updated: 4/2018; program updated 3/2018
Signed by Apple
R Studio is commercial open-source software, designed for creating and managing R applications rather than, say, doing exploratory research or testing the odd hypothesis. With frills, it can get expensive, but without frills, it’s free. The Mac version seems to be developed at the same time as Linux and Windows versions. It’s a bit of a porker (500MB plus R itself at around 130MB) and requires a separate R download; R itself is updated regularly and has a signed Mac package.
When you first load R Studio, it tells you to go back and install R. Once you've done that and restarted, it finds R easily enough, and presents you with an integrated development environment (IDE). If you try to do something, such as importing SPSS data, that isn’t possible without further downloads, it automatically connects to the Internet and installs whatever you need. The user interface is Mac-standard in most ways — you get a menu at the top of the screen (as well as menus in the window itself), and the open/save dialogues are thankfully quite normal.
Though you can manage your R installation from R Studio, it’s a tool for dealing directly with syntax, and for managing projects; it’s not a beginner’s tool (as, say, Jamovi can be). R Studio never claims to be anything but an IDE, with many options and good operating-system integration.
Current Version: 3.192 / requires OS 10.7-10.11
Older versions: 680x0; PowerPC; OS X (Universal Binary); Windows and DOS
Listing updated: 12/2016 (program updated March 2014; web site updated in 2016)
G*Power was developed by Axel Buchner to provide power analyses for the most common statistical tests in behavioral research: t-tests, F-tests (including ANOVA, regression, etc.), and Chi-squared tests. G*Power computes power values for sample sizes, effect sizes, and alpha levels; sample sizes for given effect sizes, alpha levels, and power values; and alpha and beta values for given sample sizes, effect sizes, and beta/alpha ratios.
gretl can do general statistical routines and many specialized ones; it is in our “special purpose and general math programs” page.
A collection of command-line tools that run on all Unix-like systems, including Mac OS X. See gmt.soest.hawaii.edu for details. Many of the main developers (including me) use Mac OS X. (Description by Paul Wessel)
Graphviz is the AT&T open source drawing package. The Mac OS X version and the overall project have their own web sites. The OS X version now uses the Aqua user interface. Prepare for a steep learning curve but it may be worth it if you have graphs you do frequently; not what I'd suggest for the occasional one-off though.
gnuplot is open source scientific plotting software. It is available online from many sources
Current Version: 2.2.1
Last update: 4-6-2013
Listing updated: 4-24-2018
StatCrunch is a freely available for web-based use, currently without advertisements, with a $5 per user fee for use on your own server, or $5/six months. It has the usual range of basic statistics, from t-tests to regression to ANOVA and nonparametric tests, with a wide range of graphs also available, and works from Excel or text files. StatCrunch will also store your data within reason. For those with low budgets or infrequent needs, StatCrunch's fairly easy to use interface and price are extremely attractive (it also makes sharing data easy).
Free - open source - for Mac OS X
Current version: 1.2.1
Report updated: 7/2013
Matplotlib is a pure python plotting library with the goal of making publication quality plots using a syntax familiar to matlab users. The library uses Numeric for handling large data sets and supports a variety of output backend.
On August 28 2012, John D. Hunter, the creator of matplotlib, died from complications arising from cancer treatment, after a brief but intense battle with this terrible illness. Please consider making a donation to the John Hunter Memorial Fund.
SciPy is a library of scientific tools for Python which supplements the Numeric module. SciPy includes modules for graphics and plotting, optimization, integration, special functions, signal and image processing, genetic algorithms, ODE solvers, and others.
May be compiled from source code for OS X, Linux, etc
Latest version: 7.1
Listing updated 1/2017
The Visualization ToolKit (VTK) is a system for 3D computer graphics, image processing, and visualization with several interface layers. In VTK applications can be written directly in C++, Tcl, Java, or Python.
“VTK supports a wide variety of visualization algorithms including scalar, vector, tensor, texture, and volumetric methods; and advanced modeling techniques like implicit modelling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation. Moreover, we have directly integrated dozens of imaging algorithms into the system so you can mix 2D imaging / 3D graphics algorithms and data.”
Our test survey file: The “survey file” has 1,000 cases, with 40 questions on a five-point scale, two irrelevant variables (screen width and height), and a couple of demographics (shown here as “job type” and “new or old hire”). We are planning to run the same tests on each package as time goes on.