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Opting for Open-Source? A Review of Free Statistical Software Programs

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Title: Opting for Open-Source? A Review of Free Statistical Software Programs
Language: English
Authors: Melissa A. Shepherd (ORCID 0000-0002-2008-0330), Elizabeth J. Richardson
Source: Teaching Statistics: An International Journal for Teachers. 2024 46(1):53-63.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 11
Publication Date: 2024
Document Type: Journal Articles
Information Analyses
Education Level: Higher Education
Postsecondary Education
Descriptors: Open Source Technology, Statistics, Computer Software, Computer Software Reviews, Statistics Education, Electronic Learning, Technology Uses in Education, Technology Integration, Usability, Courseware, Media Selection, Higher Education, Faculty
DOI: 10.1111/test.12360
ISSN: 0141-982X
1467-9639
Abstract: Statistical software is commonly used in undergraduate social sciences statistics courses. Due to the increase in online/hybrid courses and the cost of SPSS, instructors may wish to switch to another statistical software. We cover seven programs: Excel, Google Sheets, jamovi, JASP, PSPP, R, and SOFA. We compare programs using the following criteria: ease of download, quality of online instructions, availability of instructor resources, sophistication of analyses available, ease of use, operating system requirements, whether it uses point-and-click or code, and whether a VPAT is available. Adopting new course materials is a valuable part of instruction but time-consuming. Therefore, this review provides information about commonly available or free open-source programs so instructors can choose based on the needs of their students and/or institutions.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1408943
Database: ERIC
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  Value: <anid>AN0175055522;d8y01jan.24;2024Jan30.07:16;v2.2.500</anid> <title id="AN0175055522-1">Opting for open‐source? A review of free statistical software programs </title> <p>Statistical software is commonly used in undergraduate social sciences statistics courses. Due to the increase in online/hybrid courses and the cost of SPSS, instructors may wish to switch to another statistical software. We cover seven programs: Excel, Google Sheets, jamovi, JASP, PSPP, R, and SOFA. We compare programs using the following criteria: ease of download, quality of online instructions, availability of instructor resources, sophistication of analyses available, ease of use, operating system requirements, whether it uses point‐and‐click or code, and whether a VPAT is available. Adopting new course materials is a valuable part of instruction but time‐consuming. Therefore, this review provides information about commonly available or free open‐source programs so instructors can choose based on the needs of their students and/or institutions.</p> <p>Keywords: research methods; SPSS; statistical software; teaching statistics</p> <hd id="AN0175055522-2">INTRODUCTION</hd> <p>Statistics and research methods are cornerstone courses in the social sciences curriculum. Many institutions incorporate statistical software in instruction[<reflink idref="bib1" id="ref1">1</reflink>] which promotes development of applied skills for succeeding in the 21st century workplace.[<reflink idref="bib2" id="ref2">2</reflink>] Furthermore, inclusion of statistical software in the teaching of statistics can reduce statistics anxiety and increase achievement in course content.[<reflink idref="bib3" id="ref3">3</reflink>]</p> <p>SPSS is a statistical program commonly used for analyses in social science research[<reflink idref="bib4" id="ref4">4</reflink>] and is also frequently used in the teaching of statistics. Sahin and Aybek[<reflink idref="bib5" id="ref5">5</reflink>] note that many textbooks for teaching statistics for social sciences use SPSS, suggesting wide use in the classroom. More specifically, it is the most common statistical software used in psychology instruction, in part, due to its user‐friendly point‐and‐click interface.[<reflink idref="bib1" id="ref6">1</reflink>]</p> <p>SPSS is currently licensed through IBM with the ability to purchase time‐limited institutional and individual licenses. Many institutions purchase site‐wide yearly licenses at high cost but with free use among instructors and enrolled students. Yet even with the high price of an institutional license, accessibility may still be a concern. Some university facilities, departments, or schools allow SPSS to be downloaded to individuals' personal computers, with access ending at the yearly renewal period. However, other institutions (like ours) only allow download of SPSS to university campus computers, thus limiting accessibility to students who commute or learn remotely. This may also require students to incur additional cost of individual licenses or preclude instructional use of SPSS entirely when teaching statistics and research methods courses fully online.</p> <p>Open‐source statistical software addresses concerns of both cost and accessibility. Such programs are free to download and use across various operating platforms, avoiding recurring licensing costs. Secondly, open‐source software may increase accessibility by allowing students to use their own devices. This potentially expands opportunities for students who are otherwise limited to campus computer lab sessions.</p> <p>Although limited, available research suggests open‐source or commonly available software can be used successfully in classroom instruction. Students had positive attitudes regarding the open‐source software PSPP in high school instruction.[<reflink idref="bib6" id="ref7">6</reflink>] Similarly, students in an introductory quantitative methods course had favorable attitudes toward Google Sheets.[<reflink idref="bib7" id="ref8">7</reflink>] Farrell and Carey[<reflink idref="bib8" id="ref9">8</reflink>] demonstrate that ecology students feel more proficient and confident in Excel and R after having used them in class. When comparing the open‐source software, R, to SPSS, there was no difference in undergraduate students' anxiety about the software, positive feelings toward the software, efficacy with using the software, nor was there any difference in performance on an introductory statistics lab assignment.[<reflink idref="bib9" id="ref10">9</reflink>] Overall, open‐source statistical software can be a viable classroom instruction alternative to established proprietary software such as SPSS.</p> <p>Choosing to switch from SPSS and the process of selecting another software can be time‐intensive given multiple dimensions of student, instructor, and course‐specific needs to consider. The need for comparing newer software to established statistical software has been made known for some time.[<reflink idref="bib10" id="ref11">10</reflink>] While prior work[<reflink idref="bib11" id="ref12">11</reflink>] compared various software packages for implementing particular types of statistical analyses (e.g., structural equation modeling), instructors of statistics courses considering change would benefit from a broader review to gain familiarity with alternatives to SPSS, aid in choosing an appropriate alternative, and introduce resources to update course materials. Abbasnasab Sardareh and colleagues[<reflink idref="bib12" id="ref13">12</reflink>] compared functionality of SPSS and open‐source programs relying on a command line interface (e.g., R in RStudio) or graphical user interface (GUI) overlaid on R language (e.g., jamovi or R Commander). While thorough in regard to software programs reviewed, this work[<reflink idref="bib12" id="ref14">12</reflink>] did not discuss other existing freely available or easily accessible programs not reliant on R language or that implement GUIs that may be more suitable for the beginning student.</p> <p>To meet this need, the present paper reviews seven commonly available or open‐source SPSS alternatives (Excel, Google Forms, jamovi, JASP, PSPP, R, and SOFA) for instructors interested in transitioning from SPSS in their social science statistics courses. It focuses not only on the usability of the software but also the availability of resources for teaching to primarily serve as a starting point for instructors in the process of choosing the best SPSS alternative to meet their course and student needs. This paper is intended for instructors who have some experience with command line or code‐driven software but otherwise mostly use SPSS, have basic but not extensive knowledge regarding computer technology, and incorporate student use of statistical software in undergraduate coursework.</p> <hd id="AN0175055522-3">CRITERIA AND METHOD OF EVALUATION</hd> <p>Two psychology professors (authors) who regularly teach undergraduate introductory statistics in psychology (students in this course include: exercise and nutrition science, psychology, social work, and speech pathology majors) downloaded and evaluated the following commonly available or free open‐source statistical software packages: Excel, Google Forms, jamovi, JASP, PSPP, R, and SOFA. The authors have a combined total of more than 20 semesters of teaching the course designed around the use of SPSS in primarily face‐to‐face formats, though with three recent course sections adapted to be delivered fully online. One author (MAS) downloaded software on Windows PC 10 Version 21H1; the other author (EJR) used Mac OS Big Sur version 11.6.7. Each author conducted an independent review of the programs across eight domains, without knowledge of the other's evaluation until all reviews were complete. Evaluations included both qualitative and quantitative evaluations that were specified prior to the start of any software review. Numerical ratings produced by quantitative evaluations were averaged across both authors.</p> <p>Additionally, three senior undergraduate psychology majors who have previously taken social science statistics with instruction in SPSS downloaded the software programs. As we wanted this to be similar to class, they were provided the website download links for the programs. Additionally, they were provided with Youtube tutorials (linked in the Conclusion section) for installing R as it is a different download process. All used devices running Windows; two used laptops; and one used a tablet. Each student individually provided their scores to an author who then averaged the ratings.</p> <hd id="AN0175055522-4">Measures</hd> <p>Operating system requirements for downloading each software program were documented from respective websites. Ease of download and student ease of download was based on level of difficulty with locating the file and installing and was rated using a 1–5 Likert scale where <emph>1</emph> = very difficult and <emph>5</emph> = very easy. Quality of online instruction was assessed by the thoroughness and "user and reader‐friendliness" of resources to guide the novice and was also assessed via a 1–5 Likert scale where <emph>1</emph> = very low quality and <emph>5</emph> = very high quality. Availability of instructor resources to accompany the software was evaluated on a 1–5 Likert scale where <emph>1</emph> = very few and <emph>5</emph> = very many, as was the sophistication of analyses available (1–5 Likert scale where <emph>1</emph> = basic analyses and <emph>5</emph> = advanced analyses). We also examined ease of navigating the user interface using a 1–5 Likert scale (where <emph>1</emph> = very difficult and <emph>5</emph> = very easy) and noted whether the program uses point‐and‐click or command line/code (qualitative). Finally, we recorded whether there is a Voluntary Product Accessibility Template (VPAT) available (yes or no). A VPAT demonstrates compliance with US regulations for IT accessibility for individuals with disabilities.[<reflink idref="bib13" id="ref15">13</reflink>] We also describe rationale for ratings and other observations for each of our criterion. Note that we include some comments on quality of output and tables, but we do not examine graphic capabilities which are fast becoming of critical importance in teaching introductory statistics at high school and university levels. Examining graphic capabilities would require considerable in‐depth usage of the different software programs. Under the sophistication of analytical capabilities criterion, we identify whether the software meets the needs of most undergraduate introductory social science statistics courses, which we define as the capacity to perform basic operations and tests: measures of central tendency and variability, correlation, linear regression, independent and paired samples <emph>t</emph>‐tests, one‐way ANOVA, and chi‐square because these analyses are commonly included in introductory statistics textbooks.[[<reflink idref="bib14" id="ref16">14</reflink>], [<reflink idref="bib16" id="ref17">16</reflink>]] Analytical capabilities that may complement teaching advanced statistical coursework or be useful in individual student or instructor research are also mentioned (and earn the statistical software a higher score), though lists of statistical tools available within each program are not exhaustive. Finally, more statistical software, calculators, and online tools exist than what we review. This paper merely provides an overview of programs more commonly known and capable of analyzing social science data.</p> <hd id="AN0175055522-5">RATINGS OF SEVEN OPEN‐SOURCE OR ACCESSIBLE PROGRAMS</hd> <p>Averaged Likert scores, user interface type, and VPAT availability are found in Table 1.</p> <p>1 TABLE Summary of rater evaluations, user interface type, and VPAT availability for seven open‐source statistical software programs.</p> <p> <ephtml> <table><thead valign="bottom"><tr><th align="left" /><th align="left">Criterion</th></tr><tr><th align="left">Program</th><th align="left">Ease of download</th><th align="left">Student ease of download</th><th align="left">User resources</th><th align="left">Teaching resources</th><th align="left">Ease of use statistical</th><th align="left">Analytical capability</th><th align="left">Interface type</th><th align="left">VPAT available</th></tr></thead><tbody valign="top"><tr><td align="left">Excel</td><td align="char" char=".">5</td><td align="char" char=".">4.67</td><td align="char" char=".">3</td><td align="char" char=".">2</td><td align="char" char=".">2</td><td align="char" char=".">1.5</td><td align="left">Enter formulas in cells</td><td align="left">Yes</td></tr><tr><td align="left">Google Sheets</td><td align="char" char=".">5</td><td align="char" char=".">5</td><td align="char" char=".">2.5</td><td align="char" char=".">1.5</td><td align="char" char=".">2</td><td align="char" char=".">1</td><td align="left">Enter formulas in cells</td><td align="left">Yes</td></tr><tr><td align="left">jamovi</td><td align="char" char=".">5</td><td align="char" char=".">4.17</td><td align="char" char=".">5</td><td align="char" char=".">5</td><td align="char" char=".">4.5</td><td align="char" char=".">4.5</td><td align="left">Point‐and‐click or R language code</td><td align="left">Yes</td></tr><tr><td align="left">JASP</td><td align="char" char=".">4.5</td><td align="char" char=".">2.67</td><td align="char" char=".">5</td><td align="char" char=".">5</td><td align="char" char=".">4.5</td><td align="char" char=".">4.5</td><td align="left">Point‐and‐click</td><td align="left">Yes</td></tr><tr><td align="left">PSPP</td><td align="char" char=".">3</td><td align="char" char=".">4.33</td><td align="char" char=".">2</td><td align="char" char=".">1</td><td align="char" char=".">4</td><td align="char" char=".">3.5</td><td align="left">Point‐and‐click or command line syntax</td><td align="left">No</td></tr><tr><td align="left">R</td><td align="char" char=".">1.5</td><td align="char" char=".">4</td><td align="char" char=".">5</td><td align="char" char=".">5</td><td align="char" char=".">1.5</td><td align="char" char=".">5</td><td align="left">Code/commaand line syntax</td><td align="left">Yes</td></tr><tr><td align="left">SOFA</td><td align="char" char=".">2.5</td><td align="char" char=".">4.33</td><td align="char" char=".">2.5</td><td align="char" char=".">1</td><td align="char" char=".">4</td><td align="char" char=".">2</td><td align="left">Point‐and‐click</td><td align="left">No</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note</emph>: Numerical ratings from Likert scales represent the average between the two raters. The "Ease of Student Download" scores were averaged between three raters.</p> <hd id="AN0175055522-6">Excel</hd> <p>Excel is a propriety software of Microsoft originally released in 1997.[<reflink idref="bib17" id="ref18">17</reflink>] It is a spreadsheet software which was not designed to be used for statistical data analysis nor for statistical graphics, but it can be used to run limited statistical analyses. Excel is not free and at the time of this writing, it costs $159.99.[<reflink idref="bib18" id="ref19">18</reflink>] However, Excel is part of Microsoft 365 ($69.99 per year or $149.99 for a one‐time student purchase),[<reflink idref="bib19" id="ref20">19</reflink>] so it is plausible that students already have access to this software. Some institutions, like ours, provide access to Microsoft 365 to enrolled students, precluding the need for individual subscriptions.</p> <hd id="AN0175055522-7">Operating system requirements</hd> <p>Excel accommodates a wide range of OS requirements, including Windows 7+; mac OS X 10.6 or later. It is important to note that users of the subscription‐based service must connect to the Internet at least every 31 days or apps will go into low functionality mode.[<reflink idref="bib19" id="ref21">19</reflink>]</p> <hd id="AN0175055522-8">Download ease</hd> <p>As Excel is part of the Microsoft package, it is often included on many computers. Even if not included, the download process is straightforward.</p> <hd id="AN0175055522-9">Quality of online instruction</hd> <p>Because Excel is widely used, there are many online instructional resources for its use. Microsoft provides instruction through its support page for many statistical functions like standard deviation (https://support.microsoft.com/en-us/office/stdev-function-51fecaaa-231e-4bbb-9230-33650a72c9b0)[<reflink idref="bib20" id="ref22">20</reflink>] and correlation (https://support.microsoft.com/en‐us/office/correl‐function‐995dcef7‐0c0a‐4bed‐a3fb‐239d7b68ca92).[<reflink idref="bib21" id="ref23">21</reflink>] For video instruction, we recommend the YouTube channel by Dr. Todd Grande[<reflink idref="bib22" id="ref24">22</reflink>] which has a playlist titled "Statistics and Probabilities in Excel" (https://<ulink href="http://www.youtube.com/playlist?list=PLdlFfrVsmlvAz0kKV3EdHJtPdg8PqQYwU">www.youtube.com/playlist?list=PLdlFfrVsmlvAz0kKV3EdHJtPdg8PqQYwU</ulink>) with 114 videos.</p> <hd id="AN0175055522-10">Number of instructor resources</hd> <p>Because Excel is a Microsoft software myriad resources are available. However, few instructor resources are available specifically for use in social science courses. The limited availability of instructor resources may be attributed to the fact that few instructors exclusively use Excel, resulting in less teaching guides and datasets.</p> <hd id="AN0175055522-11">Sophistication of analyses available</hd> <p>Excel accommodates basic calculations with existing formulas (e.g., measures of central tendency and variability) which can be found under the "Formulas" tab. One can run some basic analyses, such as <emph>t</emph>‐tests, by using the Data Analysis tab and selecting the test.</p> <hd id="AN0175055522-12">Ease of use</hd> <p>Excel is easy to navigate, and data entry is straightforward. Given that it is part of a rather ubiquitous suite of applications, students may have used it previously. However, Excel is not as user‐friendly for data analysis. Analyses are found under two different tabs (formulas and analyze data) and specifying cells for calculations adds to its difficulty.</p> <hd id="AN0175055522-13">Google sheets</hd> <p>Google Sheets is offered through Google Workspace, a suite of cloud‐based programs and collaboration tools. Using a spreadsheet format like Excel, Google Sheets can also be used to run statistical analyses. Unlike Excel, however, Google Sheets for personal use is free of cost with a Google account.</p> <hd id="AN0175055522-14">Operating system requirements</hd> <p>Because Google Sheets is a web‐based spreadsheet, Internet access is required. Browsers that support the full use include Chrome, Firefox, Microsoft Edge, and Safari. Users will need a Google account to access Google Sheets, necessitating the need to create an account if students do not already have one. Downloading the extension "XLMiner Analysis ToolPak" is recommended for more advanced statistical analyses which can be accessed through the "Extensions" button in Google Sheets.</p> <hd id="AN0175055522-15">Download ease</hd> <p>With a Google account, Google Sheets is easy to access by simply logging into the website.[<reflink idref="bib23" id="ref25">23</reflink>]</p> <hd id="AN0175055522-16">Quality of online instruction</hd> <p>Similar to Excel, Google Sheets was not specifically designed for performing statistical calculations. Therefore, instructional resources are not as comprehensive, though Kunicki and colleagues[<reflink idref="bib7" id="ref26">7</reflink>] provide a list of formulas. For video instruction, Jalayer Academy[<reflink idref="bib24" id="ref27">24</reflink>] on YouTube offers a playlist titled "Statistics and Data Analysis with Google Sheets" (https://<ulink href="http://www.youtube.com/watch?v=xLQgIYe5Dss&list=PLjPbBibKHH1%5fEZ3kcJFTXDORc6mrryUER">www.youtube.com/watch?v=xLQgIYe5Dss&list=PLjPbBibKHH1%5fEZ3kcJFTXDORc6mrryUER</ulink>) that includes 31 videos.</p> <hd id="AN0175055522-17">Number of instructor resources</hd> <p>Google Sheets is also quite similar to Excel in that few teaching resources exist, such as practice datasets and assignments.</p> <hd id="AN0175055522-18">Sophistication of analyses available</hd> <p>Google Sheets can accommodate basic descriptive statistics such as measures of central tendency and variability as well as more advanced analyses like multiple regression through the XL Miner add‐on.</p> <hd id="AN0175055522-19">Ease of use</hd> <p>Google Sheets parallels Excel in its user interface, and in this way, students may find the spreadsheet easy to navigate particularly if they havepreviously used Excel. However, this similarity also incurs the same drawbacks: cell selection and formula specification adds a layer of complexity. Like Excel, basic analyses are simpler to run than more complex analyses.</p> <hd id="AN0175055522-20">Jamovi</hd> <p>The jamovi project[<reflink idref="bib25" id="ref28">25</reflink>] was created in 2016 by some of the developers of JASP to reflect advancements in software technology while maintaining a simple graphical interface similar to JASP.[<reflink idref="bib26" id="ref29">26</reflink>]</p> <hd id="AN0175055522-21">Operating system requirements</hd> <p>Windows Vista 64‐bit and above, macOS 10.9+ (Maverick) or higher, Linux, and Chromebooks. Legacy versions are available for older operating systems.[<reflink idref="bib27" id="ref30">27</reflink>]</p> <hd id="AN0175055522-22">Download ease</hd> <p>Locating and downloading the file is straightforward, with detailed instructions available in the user manual. jamovi can be downloaded at https://<ulink href="http://www.jamovi.org/download.html,">www.jamovi.org/download.html,</ulink> where the user is directed to Mac or Windows versions, depending on the device used to visit the site.[<reflink idref="bib28" id="ref31">28</reflink>] One can avoid a download altogether with a cloud‐based version, though this is still in development.[<reflink idref="bib29" id="ref32">29</reflink>] Currently, the cloud‐based beta version is freely available but limited to 45‐minute sessions and is subject to availability at the time of usage.[<reflink idref="bib29" id="ref33">29</reflink>] Users have the option to gain priority access with unlimited session limits via a priority plan requiring a monthly fee.[<reflink idref="bib30" id="ref34">30</reflink>]</p> <hd id="AN0175055522-23">Quality of online instruction</hd> <p>Several free resources are available including a web‐based manual with instructional videos (https://www.jamovi.org/user-manual.html).[<reflink idref="bib31" id="ref35">31</reflink>] A 56‐video introductory course on using Jamovi is also available[<reflink idref="bib32" id="ref36">32</reflink>] and covers data files and management, graphing, and basic statistical tests which can be found at https://datalab.cc/jamovi/.</p> <hd id="AN0175055522-24">Availability of instructor resources</hd> <p>A free statistics textbook designed for undergraduate psychology students incorporating use of jamovi is available.[<reflink idref="bib33" id="ref37">33</reflink>] This text covers probability theory, null hypothesis testing as well as descriptive statistics and basic inferential tests typical of an introductory course. The text includes user interface pictorials to guide students with analyses and can be found at https://<ulink href="http://www.learnstatswithjamovi.com">www.learnstatswithjamovi.com</ulink>. There is a jamovi module (lsj‐data) with datasets that accompany this textbook. Example assignments with datasets are also available through the Open Science Framework[<reflink idref="bib34" id="ref38">34</reflink>] among a compilation of other teaching and instructional resources through the jamovi community (https://www.jamovi.org/community.html).[<reflink idref="bib35" id="ref39">35</reflink>]</p> <hd id="AN0175055522-25">Sophistication of analyses available</hd> <p>jamovi appears comprehensive for an undergraduate statistics course and includes mixed modeling, MANOVA, logistic regression, and nonparametric tests. More complex analyses like structural equation modeling and Bayesian methods are possible with add‐on modules. The R Syntax Mode of jamovi produces the R code for specified analyses, which may be a useful primer for students who wish to later learn R. Additionally, another module (Rj) allows you to run R code within jamovi.</p> <p>Jamovi runs on the R language but with an intuitive graphical user interface similar to SPSS. An advantage is that output is produced simultaneous to specifying analyses and within the same window. Changes in results are observed as the user changes variables. Additionally, tables produced in output are suited to APA formatting.</p> <hd id="AN0175055522-26">JASP</hd> <p>JASP (Jeffrey's Amazing Statistics Program, in recognition of Harold Jeffreys)[<reflink idref="bib36" id="ref40">36</reflink>] was developed in 2013 with the goal of incorporating both Bayesian and classical methods in a graphical software alternative to SPSS.[<reflink idref="bib37" id="ref41">37</reflink>]</p> <hd id="AN0175055522-27">Operating system requirements</hd> <p>JASP accommodates Windows Vista 64‐bit and above and macOS 10.13+, Chromebook, and Linux. Older JASP versions are available for older macOS versions. You can also launch JASP 0.14.3 online via rollApp.[<reflink idref="bib38" id="ref42">38</reflink>]</p> <hd id="AN0175055522-28">Download ease</hd> <p>On the JASP webpage (https://jasp-stats.org/download/), users select their operating system and download begins automatically.[<reflink idref="bib38" id="ref43">38</reflink>] Despite having an updated operating system, one author (EJR) could only download a prior version presumably due to older hardware. This may pose difficulty for students using older devices.</p> <hd id="AN0175055522-29">Quality of online instruction</hd> <p>The user‐guide (https://jasp-stats.org/how-to-use-jasp/) links to a blog post, video, or animated GIF for each analysis available.[<reflink idref="bib31" id="ref44">31</reflink>] There are two free manuals available. <emph>Statistical Analysis in JASP 0.16.1: A guide for Students</emph> covers a range of statistical analyses and flowcharts for choosing the appropriate test.[<reflink idref="bib39" id="ref45">39</reflink>] Similarly, <emph>Exploring Diversity with Statistics: Step‐by‐Step JASP Guides</emph> demonstrates analyses with explanations of output.[<reflink idref="bib40" id="ref46">40</reflink>] Other resources, including books, papers, and workshops are linked at https://jasp-stats.org/jasp-materials/.[<reflink idref="bib30" id="ref47">30</reflink>] A blogpost is also available which links YouTube tutorials: https://jasp-stats.org/2020/02/11/how-to-use-jasp-jasp-on-youtube/.[<reflink idref="bib41" id="ref48">41</reflink>]</p> <hd id="AN0175055522-30">Availability of instructor resources</hd> <p>Walker and colleagues[<reflink idref="bib40" id="ref49">40</reflink>] provide datasets for undergraduate introductory statistics instruction, and the JASP website (https://jasp-stats.org/teaching-with-jasp/) includes a page devoted to teaching resources.[<reflink idref="bib42" id="ref50">42</reflink>] There are over 50 datasets available as well as a free textbook[<reflink idref="bib43" id="ref51">43</reflink>] and other resources for undergraduate students.</p> <hd id="AN0175055522-31">Sophistication of analyses available</hd> <p>JASP is sufficient for undergraduate instruction and includes advanced capabilities such as factor analysis, mixed modeling, mediation, and meta‐analysis (via add‐on modules).</p> <hd id="AN0175055522-32">Ease of use</hd> <p>The interface is intuitive with somewhat less complicated menus compared to SPSS but maintains similarities to render a seamless switch to JASP. Output is provided in real time beside the analyses selection pane, like jamovi. Tables are also created in APA format. However, datafiles must be imported and cannot be edited within JASP; editing must occur within the original file.</p> <hd id="AN0175055522-33">PSPP</hd> <p>PSPP[<reflink idref="bib44" id="ref52">44</reflink>] was made available in 1997 as an SPSS replacement.[[<reflink idref="bib45" id="ref53">45</reflink>]] As such, PSPP is designed to look and function similarly to SPSS. PSPP can be downloaded at https://www.gnu.org/software/pspp/get.html.[<reflink idref="bib47" id="ref54">47</reflink>]</p> <hd id="AN0175055522-34">Operating system requirements</hd> <p>Recommended platforms are free operating systems like GNU or Linux. While PSPP will likely work on Windows and Mac OS, support for free systems is prioritized over proprietary operating systems, though crowdsourcing efforts to improve compatibility across platforms are welcomed.[<reflink idref="bib47" id="ref55">47</reflink>] While PSPP could open on one of our devices (Mac OS Big Sur, v 11.6.7), it unexpectedly quit when attempting to run an analysis.</p> <hd id="AN0175055522-35">Download ease</hd> <p>The user must locate PSPP among many other programs on the GNU website. All released versions of PSPP are available, and according to an independent tutorial,[<reflink idref="bib48" id="ref56">48</reflink>] users often need a binary version and either the 32‐ or 64‐bit depending on their device's age. Instructions may be unclear for those less savvy about software and operating systems. When downloading on Mac OS, the author had to override the security settings to open and run PSPP. Download may be seamless on a GNU operating system rather than Windows or Mac OS.</p> <hd id="AN0175055522-36">Quality of online instruction</hd> <p>PSPP has both a developer's manual[<reflink idref="bib46" id="ref57">46</reflink>] describing files that PSPP supports as well as a user's manual[<reflink idref="bib49" id="ref58">49</reflink>] that provides code/syntax as well as instruction on using the graphical user interface. The user's manual is found at https://<ulink href="http://www.gnu.org/software/pspp/manual/pspp.pdf">www.gnu.org/software/pspp/manual/pspp.pdf</ulink>. Fisk[<reflink idref="bib48" id="ref59">48</reflink>] created an independent tutorial for psychology students with greater focus on the graphical user interface. This tutorial instructs users on basic data management as well as statistical tests commonly used in introductory statistics courses and is found at https://<ulink href="http://www.garyfisk.com/pspp/index.html">www.garyfisk.com/pspp/index.html</ulink>. While the quality of this particular tutorial appears high, our ratings reflect the limited number of user resources available overall.</p> <hd id="AN0175055522-37">Availability of instructor resources</hd> <p>A student tutorial on statistical procedures is available at http://ssric.org/node/699.[<reflink idref="bib50" id="ref60">50</reflink>] Nelson[<reflink idref="bib51" id="ref61">51</reflink>] has also created freely available PSPP lab exercises with a dataset at <ulink href="http://ssric.org/node/559">http://ssric.org/node/559</ulink>.</p> <hd id="AN0175055522-38">Sophistication of analyses available</hd> <p>PSPP is more limited in analytical capabilities within its point‐and‐click interface relative to SPSS, though it performs basic descriptive and inferential procedures sufficient for an introductory course. MANOVA, random‐effects, and mixed modeling capabilities are not available. PSPP seeks assistance from the public at large to contribute code for improving analytical capabilities and functionality.</p> <hd id="AN0175055522-39">Ease of use</hd> <p>Menu and selection panes are deliberately similar to SPSS, resulting in greater familiarity if switching from SPSS save some differences (e.g., Spearman's rho is performed through the crosstabs function and not under the correlation menu).</p> <hd id="AN0175055522-40">R</hd> <p>The programming language of R was developed in 1991with R becoming freely available via RStudio in 1995.[<reflink idref="bib52" id="ref62">52</reflink>]</p> <hd id="AN0175055522-41">Operating system requirements</hd> <p>Windows 10/11, macOS 10.15+, Ubuntu 18+/Debian 10+, Ubuntu 22, Fedora 19/Red Hat 7, Fedora 34/Red Hat 8, and OpenSUSE 15.[<reflink idref="bib53" id="ref63">53</reflink>]</p> <hd id="AN0175055522-42">Download ease</hd> <p>The download process is multistep beginning with visiting a comprehensive R archive network (CRAN) at https://cran.r-project.org/ and selecting the appropriate operating system.[<reflink idref="bib54" id="ref64">54</reflink>] Download should occur from the nearest secure CRAN mirror site (distribution site for code and documentation for R). As this process will probably be unfamiliar to most people, a tutorial may be helpful. For Windows users we suggest https://<ulink href="http://www.youtube.com/watch?v=TFGYlKvQEQ4&t=42s[55]">www.youtube.com/watch?v=TFGYlKvQEQ4&t=42s[55]</ulink> and for Mac users https://<ulink href="http://www.youtube.com/watch?v=LanBozXJjOk.[56]">www.youtube.com/watch?v=LanBozXJjOk.[56]</ulink></p> <hd id="AN0175055522-43">Quality of online instruction</hd> <p>Myriad resources exist for learning R including numerous books: https://www.bigbookofr.com/index.html[<reflink idref="bib57" id="ref65">57</reflink>] as well as webinars, tutorials, and videos: https://education.rstudio.com/learn/beginner/.[<reflink idref="bib58" id="ref66">58</reflink>]</p> <hd id="AN0175055522-44">Availability of instructor resources</hd> <p>Teaching resources are extensive, and there is a complete undergraduate course available replete with datasets, slides, assignments, and sample exams.[<reflink idref="bib59" id="ref67">59</reflink>] Teaching resources for R can be found at https://education.rstudio.com/teach/materials/.</p> <hd id="AN0175055522-45">Sophistication of analyses available</hd> <p>R capabilities extend well beyond that required for undergraduate coursework. The large R community has produced numerous extensions allowing for complex statistical analyses like Hierarchical Linear Modeling.</p> <hd id="AN0175055522-46">Ease of use</hd> <p>R requires coding, which may create a steeper learning curve for the novice. This may translate to the instructor teaching code as an ancillary course goal to statistical concepts. However, R Commander is a GUI that may circumvent this issue and is freely available as an R package and can also be obtained from a CRAN. A basic guide to the use of R Commander is freely available from its developer, John Fox, at McMaster University and can be found at https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/Getting-Started-with-the-Rcmdr.pdf. RStudio, an integrated development environment to R, also provides a simpler interface with multiple features to facilitate learning R language, including automatic code completion. Download of R is first required before downloading RStudio, which can be done by visiting https://posit.co/download/rstudio-desktop/.</p> <hd id="AN0175055522-47">SOFA</hd> <p>SOFA (Statistics Open For All)[<reflink idref="bib60" id="ref68">60</reflink>] was released in 2009[<reflink idref="bib61" id="ref69">61</reflink>] and is designed to teach statistics as the user engages with the software.</p> <hd id="AN0175055522-48">Operating system requirements</hd> <p>SOFA works on Windows 11 and Linux systems.[<reflink idref="bib62" id="ref70">62</reflink>] The newest version (available since May 2019) is not available for MacOS and the older version is no longer compatible with new MacOS operating systems (e.g., Monterey—12.2.1).[<reflink idref="bib62" id="ref71">62</reflink>] This is a drawback since 40% of college students use Macintosh devices[<reflink idref="bib63" id="ref72">63</reflink>] and presumably a significant number of instructors do as well.</p> <hd id="AN0175055522-49">Download ease</hd> <p>Download was simple for the Windows user but not possible for the Mac user because of the MacOS limitations noted above.</p> <hd id="AN0175055522-50">Quality of online instruction</hd> <p>The SOFA website, https://<ulink href="http://www.sofastatistics.com/home.php,">www.sofastatistics.com/home.php,</ulink> contains 12 YouTube videos as well as step‐by‐step screenshot guides.[<reflink idref="bib61" id="ref73">61</reflink>]</p> <hd id="AN0175055522-51">Availability of instructor resources</hd> <p>A free lab manual[<reflink idref="bib64" id="ref74">64</reflink>] is available: <ulink href="http://www.ssric.org/files/2021-03/G%5fSELF%5fLabManual%5fNew.pdf,">http://www.ssric.org/files/2021-03/G%5fSELF%5fLabManual%5fNew.pdf,</ulink> though no additional instructor resources were found.</p> <hd id="AN0175055522-52">Sophistication of analyses available</hd> <p>Only nine analyses are available (ANOVA, chi‐square test of independence, Pearson's correlation, Spearman's correlation, Kruskal–Wallis H, Mann–Whitney <emph>U</emph>, independent samples <emph>t</emph>‐test, dependent samples <emph>t</emph>‐test, and Wilcoxon signed ranks). Basic analyses like linear regression and Cronbach's alpha are not available.</p> <hd id="AN0175055522-53">Ease of use</hd> <p>SOFA aids the user in determining the appropriate test for analysis. Importing a dataset was simple and intuitive, but one author needed to view a tutorial to successfully enter data.</p> <hd id="AN0175055522-54">CONCLUSION</hd> <p>Free statistical software is increasingly considered for undergraduate instruction to improve accessibility, avoid high costs, and improve adaptability to online and hybrid courses. We evaluated seven alternatives to SPSS to select a free program best suited for our social science instructional needs and share our findings with others considering a transition. Overall, jamovi scored well across domains, and thus we chose to adopt it for our classes.</p> <p>Jamovi, Excel, and Google Sheets earned the highest scores for ease of download by the authors. Interestingly, students gave a score of 4 or above to all of the programs except for JASP suggesting that overall the downloading process went smoothly. Notably, the largest discrepancy between authors' and students' ratings was for R. The authors found links and instructions for download themselves, whereas students were provided with those resources. Students' ability to download these programs without assistance may attest to the benefit of additional resources like YouTube videos. Alternatively, students may be more comfortable with technology than faculty. Therefore, any of these software programs will accommodate teaching an online course requiring students to download the program to their own device rather than using a university computer. All software had similar operating system requirements sans SOFA which does not work with MacOS. As many students and faculty are likely to use Apple devices, this is a major limitation to SOFA. Finally, a VPAT is available for Excel, Google sheets, jamovi, JASP, and R, which is important for many US‐based institutions.</p> <p>Jamovi, JASP, and R had the highest scores for online instructions. It is likely that few instructors, particularly those who did not graduate recently, have received formal training in using these software programs. Because of this, the availability of comprehensive online resources for learning the programs may be helpful for instructors and students alike. jamovi, JASP, and R had the highest scores for teaching resources and thus would be recommended for first‐time statistics instructors who may benefit from the extensive availability of practice databases and pre‐constructed assignments. Likewise, veteran instructors who are switching may also benefit from these resources if they want to expand their collection of class activities.</p> <p>R scored the highest for sophistication of analyses, while point‐and‐click software programs scored higher than code‐based ones for ease of use with jamovie scoring the highest. Adopting R may necessitate more teaching time than instructors have available in order to properly teach coding. On the other hand, learning to code affords an applied skill useful in other contexts and may be helpful for students entering PhD programs given its increasing use in the field.[<reflink idref="bib65" id="ref75">65</reflink>] Instructors who allocate more time to teaching students how to perform analyses by hand and/or on the theoretical basis of analyses will likely have less time to provide coding instruction for programs like R. In these cases, point‐and‐click options may be preferable. While the interface of jamovi is point‐and‐click, it also has the option to use and produce R code and thus provides greater latitude for instructors who want to expose students to both options. For example, novice statistics students could use jamovi's point‐and‐click interface but later incorporate its R‐coding capabilities in more advanced statistics courses. It should be noted, however, that R Commander and RStudio afford similar benefits in offering a more user‐friendly interface and conduit to learning the R language.</p> <p>Overall, we did not give much consideration to the spreadsheet programs, Excel and Google Sheets, because of their limited analytic capabilities and added difficulty of cell and formula specification due to the fact that they were not designed for statistical use. However, Warner and Meehan[<reflink idref="bib66" id="ref76">66</reflink>] argue for Excel over SPSS because students are more likely to encounter spreadsheet programs in a broader array of future careers rather than a software dedicated to statistical analysis. In this way, these two programs offer greater generalizability beyond the statistics curriculum.</p> <p>Another issue for instructors to consider is the quality of output, particularly in relation to statistical output which may depend on the field within which the statistics course is taught. For example, students in the social sciences may require APA formatted tables in papers and manuscripts. Output from Google Sheets or Excel is not in this format and students typically must export statistical values to fully create tables. SOFA and PSPP produce tables that may require further editing and, in the case of PSPP, is often multistep: tables must be first exported to an OpenDocument file which then can be pasted into Word document for editing. JASP and jamovi both offer APA‐ready tables which can be copied over to a word processing document. APA‐formatted ANOVA and regression tables are available through R with an additional package (apaTables which can be found at a CRAN), though additional steps may be necessary to obtain the needed output. R requires a second command to view linear regression coefficients, while such output in JASP and jamovi is produced simultaneously to analysis specification and viewable within the same window.</p> <p>After careful deliberation, we chose to switch from our long‐standing use of SPSS to jamovi. We were deciding between jamovi and JASP because they are point‐and‐click without the need for additional add‐on packages (e.g., adding R Commander) and scored high across the categories. Though it is interesting to note that students did rate JASP poorly in installation ease compared to the other software programs. Importantly for us, jamovi and JASP both have a VPAT as that is a requirement for our university. We decided to switch to jamovi as it has greater potential value over JASP as a translational tool for R. In this regard, our evaluation of jamovi is consistent with Abbasnasab Sardareh and others[<reflink idref="bib12" id="ref77">12</reflink>] in its suitability for the novice user most characteristic of the introductory statistics student. Another nice feature of jamovi is an add‐on module (statkat) that provides guidance of which statistical test to run. Finally, we thought the ability to enter and edit data within jamovi to be useful in classroom instruction. For further comparison of jamovi and JASP, Alexander Swan[<reflink idref="bib67" id="ref78">67</reflink>] has created a helpful video: https://<ulink href="http://www.youtube.com/watch?v=qhlXwY0mrZw">www.youtube.com/watch?v=qhlXwY0mrZw</ulink>. Additionally, Sahin and Aybek[<reflink idref="bib5" id="ref79">5</reflink>] introduce university instructors to jamovi from installation and how to conduct common analyses which is a great resource for those who do choose to switch to jamovi.</p> <p>It is our hope that amid myriad SPSS alternatives, this review will help others simplify the process of choosing an alternative to SPSS. Software development, capability, and availability are constantly evolving and thus this review is more appropriate as a starting guide rather than a comprehensive guide for making a final decision on software selection. As there are other statistical software programs available, this review may also provide a template for instructors wishing to choose from other software programs. We found contemplating our six criteria worthwhile, and others may also find it a useful exercise. While we ultimately decided on using jamovi, we recognize that others may prioritize different features based on their course goals, students, and institutional requirements that would justify a different selection.</p> <hd id="AN0175055522-55">ACKNOWLEDGEMENTS</hd> <p>We thank Rachel Crandell, Aleigha Dunn, and Jessica Seymour for their assistance.</p> <ref id="AN0175055522-56"> <title> REFERENCES </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Davidson H, Jabbari Y, Patton H, O'Hagan F, Peters K, Cribbie R. Statistical software use in Canadian University courses: Current trends and future directions. 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  Data: Opting for Open-Source? A Review of Free Statistical Software Programs
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  Data: <searchLink fieldCode="AR" term="%22Melissa+A%2E+Shepherd%22">Melissa A. Shepherd</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-2008-0330">0000-0002-2008-0330</externalLink>)<br /><searchLink fieldCode="AR" term="%22Elizabeth+J%2E+Richardson%22">Elizabeth J. Richardson</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Teaching+Statistics%3A+An+International+Journal+for+Teachers%22"><i>Teaching Statistics: An International Journal for Teachers</i></searchLink>. 2024 46(1):53-63.
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: 11
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  Data: 2024
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  Data: Journal Articles<br />Information Analyses
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  Data: <searchLink fieldCode="DE" term="%22Open+Source+Technology%22">Open Source Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Software%22">Computer Software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Software+Reviews%22">Computer Software Reviews</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics+Education%22">Statistics Education</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Integration%22">Technology Integration</searchLink><br /><searchLink fieldCode="DE" term="%22Usability%22">Usability</searchLink><br /><searchLink fieldCode="DE" term="%22Courseware%22">Courseware</searchLink><br /><searchLink fieldCode="DE" term="%22Media+Selection%22">Media Selection</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Faculty%22">Faculty</searchLink>
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  Data: 10.1111/test.12360
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  Data: 0141-982X<br />1467-9639
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Statistical software is commonly used in undergraduate social sciences statistics courses. Due to the increase in online/hybrid courses and the cost of SPSS, instructors may wish to switch to another statistical software. We cover seven programs: Excel, Google Sheets, jamovi, JASP, PSPP, R, and SOFA. We compare programs using the following criteria: ease of download, quality of online instructions, availability of instructor resources, sophistication of analyses available, ease of use, operating system requirements, whether it uses point-and-click or code, and whether a VPAT is available. Adopting new course materials is a valuable part of instruction but time-consuming. Therefore, this review provides information about commonly available or free open-source programs so instructors can choose based on the needs of their students and/or institutions.
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      – TitleFull: Opting for Open-Source? A Review of Free Statistical Software Programs
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