| Edition | Target User | Key Add-ons | |---------|-------------|--------------| | SPSS Statistics Base | Students, basic research | Descriptive stats, bivariate tests, linear regression. | | SPSS Standard | Social/health sciences | Adds advanced regression, clustering, factor analysis. | | SPSS Professional | Market researchers | Adds custom tables, missing value analysis. | | SPSS Premium | Data scientists | Includes all add-ons: forecasting, decision trees, complex samples, conjoint, neural networks, bootstrapping. |
Free trial (14 days) and a “Student Version” (feature-limited, smaller dataset cap) are available.
| Column | Meaning |
|--------|---------|
| Levene’s Test | Check significance. If p > 0.05, use "Equal variances assumed" row. |
| t | Test statistic (larger = stronger evidence). |
| df | Degrees of freedom. |
| Sig. (2-tailed) | The p-value. If < 0.05, result is statistically significant. |
| Mean Difference | Raw difference between groups. | ibm spss
| Problem | Likely fix | |---------|-------------| | SPSS won't compute mean | Variable is set as String (text) – change to Numeric in Variable View. | | Percentages don't add to 100% | You used Valid Percent (excludes missing) instead of Percent. | | Graphs look wrong | Check Measure (Scale/Ordinal/Nominal) in Variable View. | | Can't run t-test | Grouping variable must have only 2 defined values. | | Output table cut off | Double-click table → drag column borders, or export to PDF. |
Example 1: T-test (compare male vs female income) | Edition | Target User | Key Add-ons
Example 2: Chi-square (gender vs voting preference)
Example 3: Pearson correlation (age and satisfaction score) Example 1: T-test (compare male vs female income)
Most unstructured data in the world exists as text—survey comments, social media posts, call center logs. SPSS Text Analytics uses natural language processing (NLP) to extract concepts, sentiments, and categories from open-ended text.