Top 10 New IBM SPSS Statistics Features - dummies

Top 10 New IBM SPSS Statistics Features

By Keith McCormick, Jesus Salcedo, Aaron Poh

SPSS Statistics adds new features with every new version. There are more than ten features to talk about, but here is a list of the ten that are the most recent and most exciting:

  • Generalized Spatial Association Rule (GSAR): One of the new GeoSpatial Modeling Wizard options allows you to build a Time Series model using geomapping information. The idea is to map events taking place in space over slices of time. For instance, a lot of urban crime is at night, but suburban breaking-and-entering crimes tend to happen during the workday.

  • Spatio-Temporal Prediction (STP): This is another new menu in the GeoSpatial Modeling Wizard. This technique allows you to create linear models when data has been collected over a long period of time at different locations.

  • Temporal Causal Modeling (TCM): A whole new Forecasting menu. It uses a wizardlike environment to help you add the best predictors to your Time Series models.

  • Completely redesigned web reports: Version 23 brings with it the new Web Report with a lot more interactivity. And because it’s web based, you don’t have to worry about the recipient having a copy of SPSS.

  • A wider range of R programming options: The combination is really proving powerful, so SPSS now allows you to call SPSS from R.

  • Compare Subgroups Plot: Another bit of big news in this release is that there are a ton of new programmability plug-ins in the menus. IBM has written these for you so you don’t have to know any Python. In fact, you don’t really have to know where they came from except that you have to select Install Python when you install Version 23. As an example, there is a nifty plot in the Graphs menu that automatically chooses appropriate graphic based on the Level of Measurement of the variables.

  • Split into Files: Another one of the Python plug-in macros. It makes it super easy to create files for each category in a categorical file — for instance, you may want to create a file for new customers and a separate file for established customers.

  • Create Dummy Variables: Another great Python plug-in. This one creates true/false variables for each category in a categorical variable. This is a requirement in Regression. Many people have been doing this manually for years, but this plug-in makes it easier. Yay!

  • SPSS Statistics output on smart devices: SPSS output on your smartphone or iPad. It’s here!

  • Styling Output: There are a couple of great Version 22 features that you may not be using yet. This is a fantastic recent addition that hasn’t gotten enough attention. You can conditionally format your pivot tables — for instance, all percentages above 80 percent could be highlighted.