14 contrasting features of top 4 statistics programs
Data wranglers must know the top features of popular statistics software. Yes, Stata, R, SAS, and SPSS—these are the softwares we will discuss. In this blog we compare 14 generic features such as execution of commands, ease of learning, menu options, range of statistical options, data interpretation, price and more to help you in your academic statistics. The article compares only the important statistical features and does not delve deep into other technical aspects of the software program. Refer our webpages on biostatistics, econometrics, and big data analytics as well and reach us at info@phdassistance.com.
| 1 | Program Features | IBM SPSS Statistics | SAS Analytics | R Programming | STATA SE |
| 2 | Execution of commands | Provides menu based options for executing commands. Offers variety of features and best of all the remaining three programs mentioned in this table. | Latest release dropped menu option in favor of command line interface (IML). | Uses command line (RCmdr) and not smooth as R requires additional plug-ins to be loaded. | Provides menu based options for executing commands but not as convenient as SPSS. |
| 3 | Ease of learning | You can learn to perform an average variety of analyses fast. Time taken to learn is short when compared to other programs. | Takes comparatively longer time to learn to do analyses. Hence, they have menu based interface. | Takes comparatively longer time to learn to do analyses. Hence, they have menu based interface. | Takes comparatively average time to learn to do analyses. Between SPSS and SAS, R. |
| 4 | Menu-bar procedures | Leader in offering menu based procedures. Consider ANOVA as an example. | Offers comparatively little depth in their menu based options. | Offers comparatively little depth in their menu based options. | Offers comparatively little depth in their menu based options. |
| 5 | Scope of statistical procedures | Limited scope of statistical procedures when compared to STATA, R, and SAS. | Offers a broader span of statistical procedures. | Offers a broader span of statistical procedures. | Offers a broader span of statistical procedures. |
| 6 | Range of output options | Broader span of output options for descriptive statistics. | Wide range of output options. | Narrow focus on the primary results of an procedure. Takes another command for additional output. | Offers a broader span of output specifications. |
| 7 | Formatting style changes | Offers you a close formatting style to the American Psychological Association (APA) style manual; however, requires some little work. For example, tables. | Unlike SPSS, SAS offers negligible formatting to that of APA. | Unlike SPSS, R Technology offers negligible formatting to that of APA. | Unlike, SPSS, Stata offers negligible formatting to that of APA. |
| 8 | Graphical output | Limited range of graphical output compared to R. User may need to use additional third-party charting software. | Limited range but offers impressive graphical output provided statistician has the skills. | Offers impressive graphical output provided you have the skills to perform those tasks. | Limited range of chart types but offers high quality and user need not have degree of skills to generate those charts. |
| 9 | Computing large data sets | Slow. Offers disk paging when memory runs low. Takes long time to complete such intensive tasks. | Database capable of handling large data sets and hence SAS is used for data mining. | Compared to SAS, database is not tuned to handle large data sets. | Slow. Offers disk paging when memory runs low. Takes long time to complete such intensive tasks. |
| 10 | Data importation capacity | Capable of importing data from SAS, R, and Stata along with Excel, Access, and Dbase. | Capable of importing data from SPSS, R, and Stata along with Excel, Access, and Dbase. | Has the best data importation capability compared to other three mentioned in this table. | Capable of importing data from SPSS, R, and SAS along with Excel, Access, and Dbase. |
| 11 | Exporting results | Best of all the remaining three mentioned in this table. Exports to MS applications and Adobe PDF. Cut and paste option available. | Version 12 can export to Excel only. Cut and paste option available. | Cannot export to MS applications and Adobe PDF. Cut and paste option available. | Version 12 can export to Excel only. Cut and paste option available. |
| 12 | Data interpretation (output) | Results agree with remaining three programs and the output is well formatted. | Results agree with remaining three programs but the formatting is not good. | Results agree with remaining three programs; however, R is more granular and requires explicit specification of the output desired | Requires further more follow up commands to get the output that is automatically produced by other programs mentioned in this table. |
| 13 | Tinkering data sets | Excellent and quickly produces immediate data sets. | Not easy. Uses command line mode instead of the Analyst menu. | Tedious. Limited to command line operations. | Second best option after SPSS in manipulating the data sets. |
| 14 | Documentation manual | Not adequate in its documentation. | Very good and heavily documented. | Not comprehensive. | Apt amount of info available and the info is effective in communicating to the read. However, not extensive. |
| 15 | Subscription price (refer our price for statistical services) | Price varies based on users, seats, or licenses. Most expensive program. Base subscription is priced at $1,188 USD/year. Technical specifications and functionalities vary. | Priced at $8700 USD for basic analytics package for windows. Price varies based on users, seats, or licenses. Technical specifications and functionalities vary. | A GNU based open source project. | Priced at $1695 USD for business single user, perpetual license. Annual price is $845 USD. Price varies based on users, seats, or licenses. Technical specifications and functionalities vary. |
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