SPSS stands for Statistical Package for the Social Sciences, a software which is widely used as an Statistical Analytic Tool in the Field of Social Science, Such as Market research, Surveys, Competitor Analysis, Healthcare, Government, Education, and others. This tool first launched in 1968, in the dark ages of computing, before we had discovered the ability to point and click. In those days, the only way to communicate with SPSS was to type in commands and parameters using the SPSS Syntax language. Since then, SPSS has come a long way: Click here to read the SPSS story, as illustrated in the diagram below.
SPSS is a powerful statistical software platform that enables you to effectively manage your data, run a wide range of statistical procedures that help you make a decision, understand and interpret your data, and prepare excellent informative reports.
Before listing SPSS tasks, let’s check the number of scholarly articles found on Google Scholar, for data science software. Only those with more than 1,700 citations are shown, in the figure below.
As we see, SPSS is by far the most dominant package, as it has been for over 20 years. This may be due to its balance between power and ease-of-use. Moreover, SPSS:
- is easy to use with its functionality of point-and-click
- offers liable and fast answers
- is very dynamic and produces useful tables and graphs
- offers a wide variety of languages
- can open data from many sources
- has large number of statistical tests
- offers many functions of advanced and basic statistics on a single integrated interface
- creates charts, tables, and decision trees ready for publication in a single tool
- can perform any analysis of a large amount of data and variables
- displays results in a separate window
- allows building any prediction model through advanced techniques
- integrates with Open Source: Use R and Python to improve SPSS syntax through specialized extensions
How SPSS Operates – SPSS Interface
When you use SPSS, you work in one of four windows: the data view, the variable view, the output view, and the syntax view. The data view displays your actual data, where columns represent variables and rows represent cases (or records). The variable view window contains the definitions of each variable in your dataset, including its name, type, label, size, alignment, and other information. The output window is where you see the results of your various queries such as frequency tables, crosstabs, statistical tests, and charts. The syntax window displays syntax, which is basically the actual computer code that produces a specific output. SPSS was originally invented as a programming language. Although most of your daily work will be done using the graphical interface, from time to time you will want to replicate your analysis. In the syntax window, you can preserve the exact steps of a particular analysis; i.e., the code used to generate any set of tables and charts.
Watch the video to see how you can use the four windows.
As you can see, if you have worked with MS Excel, you are probably used to seeing all your work on one page, charts, data, and calculations. In SPSS, each window handles a separate task.