IBM SPSS Statistics


Analytics that help you understand, prepare and analyze data.

Key Features

  • Descriptive statistics: Summarize and standardize scale variables using the descriptives procedure. Study relationships between scale and categorical variables using procedures such as means, summarize, and OLAP cubes.
  • Prediction models: Model the value of a dependent variable based on its relationship with predictor variables using procedures such as linear, ordinal or partial least square regression.
  • Data preparation: Use advanced techniques to streamline the data preparation stage – delivering faster analysis and accurate conclusions.
  • Correlations: Measure how variables are related to each other using procedures like bivariate correlations or partial correlations.
  • Classification: Reveal natural groupings or clusters within a data set that would otherwise not be apparent using exploratory tools such as two-step, hierarchical or k-means cluster analysis procedures.
  • Bootstrapping: Derive robust estimates of standard errors and confidence intervals for estimates including mean, median, correlation coefficient and regression coefficient.
  • Graphs and charts: With Chart Builder you can build drag and drop chart types from a predefined gallery onto the canvas. You can also use tools such as ROC analysis to assess the accuracy of model predictions by plotting sensitivity vs (1-specificity) of a classification test.
  • Output options: Save the results of your analysis in multiple formats including HTML, text, Word, RTF, Excel, PowerPoint (97 or later), and PDF. Quickly export charts to one of the supported graphics formats.


IBM SPSS Statistics comes in two deployment options: IBM SPSS Statistics Subscription and IBM SPSS Statistics 27, a perpetual license.

Best For

For organizations looking to optimize their entire analytics process including data preparation, descriptive statistics, linear regression, visual graphing and reporting.


IBM® SPSS® Statistics Base Edition provides capabilities that support the entire analytics process including data preparation, descriptive statistics, linear regression, visual graphing and reporting.

You can access multiple data formats without any data processing size limits. Advanced data preparation capabilities help eliminate labor-intensive manual tasks. Use over 30 analytical procedures such as bivariate statistics procedures, factor and cluster analysis, and bootstrapping. You can also extend your capabilities with R or Python.


  • Moses G

    With IBM SPSS Statistics software I have been able to perform mean, mode, correlation, ANOVA, and regression with ease and faster. I do not have to know the formulas for calculating this which makes my work very easy. It gives me the highest accuracy and the ability to generate graphs, charts, histograms, and pie-charts give me good interpretation algorithms.

  • Anoj A

    One of the best prospects of using SPSS is simpler, easy to understand the output. The best part of this software is easy to import the data. It has improved the capacity to read the data, ignores the unnecessary characters also even reads the spacing. I have used SPSS to analyze the biological data, generate the graphs, flag the significance level, etc. Graphics of the diagram and the software is awesome.

  • Yusuf A

    Can upload excel and copy data into the SPSS. Can even copy-paste which is not available on R and Python easily. Time series tools are automatic such as ARIMA whereas in Eviews they have to be checked for lags. Additionally, the processing seems fast and since it is used universally, it is available at nearly all institutions.