I used the BioC API to download the articles see the References section below of which only 40, mentioned the use of at least 1 statistical software. This is in contrast with R and Prism, which were mentioned more commonly in papers published in high impact journals. The graph below shows that SPSS is still ranking number 1 for the past 6 years, R is in second position and Prism is third. This trend was calculated only for statistical packages with more than mentions over the past 6 years, because otherwise, this number will be reflecting the noise more than the trend.
In order to answer this question, I compared the type of statistical software used in articles published in low versus high impact journals. I collected the journal impact factor for 32, of the articles and divided the dataset into 2 parts:.
I chose the threshold of 3 for no particular reason other than it seamed a reasonable limit, and also separates the dataset into 2 approximately equal subsets in terms of number of articles. Free Data Science Course. Login details for this Free course will be emailed to you. Email ID. Contact No. SPSS is basically software that is used in statistical analysis.
It is an abbreviation for Statistical Package for the Social Sciences. It is also used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations and data miners. SPSS was developed for the social sciences and was the first statistical programming language for the PC.
SAS is a programming language and has a suite developed for advanced analytics, business intelligence, data management and predictive analysis. It stands for Statistical Analysis System.
SAS was developed at North Carolina State University and was primarily developed to be able to analyze large quantities of agriculture data.
SPSS is an amazing tool for people who are not statisticians. It has a user-friendly interface and has easy to use drop-down menus. It can be used in many fields, but it mainly plays an important role in social sciences. SAS is supposed to have a large amount of high-quality production code for various purposes. It is considered to be leading in the commercial analytical space.
In more recent versions, the software is developed by IBM, strongly in the direction of a tool which accomplishes evaluations that can be largely automated and do not require special method knowledge from the user. In addition, the short release cycle has negatively impacted stability in the past.
While SPSS comes with some more specific modules e. STATA is a commercial statistical software that is particularly favored by econometricians. Considerable discounts are available when purchasing multiple licenses, and special conditions apply for the education sector. Conclusion Although STATA is a mature, very stable, and powerful software, its distribution - especially in companies - is low. For users who value a broad spectrum of methods, stability, a mature operating concept including scripting language and a fair price, STATA is superior to the more expensive commercial competition.
The five programs discussed above are the undisputed market leaders in the field of universally-applicable statistics programs, and they cover almost the entire spectrum of statistical methods. There are also several programs that have specialized in certain methods, and have thus been able to establish themselves for certain applications.
Some of these programs are mentioned - briefly - below:. In addition, there are a number of commercial and open source programs that specialize in data mining methods. What's the Best Statistical Software? R R is a popular, open-source statistics environment that can be extended by packages almost at will.
Very good community support, as well as fee-based support via third-party providers Extensive help resources freely available manuals, tutorials, and so on Very powerful and flexible scripting language e. Python Python is a fully functional, open, interpreted programming language that has become an equal alternative for data science projects in recent years. Strengths Powerful, fully-functional programming language Offers the potential for object-oriented, structured, and functional concepts Mature programming language, resulting in unit tests and debugging functionalities, for example A large number of stable packages in the data science sector and beyond Readable, clean syntax Constant development by a large developer community Full availability of the latest Deep Learning and Machine Learning methods Very easy to automate e.
SAS SAS Institute offers a professional statistics software that is commonly used in biometrics, clinical research, and in the banking sector.
Strengths Fast integration of new statistical methods, very stable and reliable routines Very good documentation and professional support Numerous modules and interfaces are available, as well as their own Business Intelligence Software for a fee Well-suited for handling large data sets Extensive in-house training offered Weaknesses Different, partly complicated but powerful program languages Partially obsolete interface, GUI optional.
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