How to use SAI Statistics?
Enter your data, choose your analysis, interpret the results. The fastest way to do statistical analysis without writing code — explained in seven steps.
Enter your data
Type directly into the data table, copy and paste from tools like Excel or Google Sheets, or import a CSV/Excel file. Columns are detected automatically and the table is ready to use instantly.
- Copy-paste support for Excel / Google Sheets
- Automatic column detection
- CSV import
| id | grup | yas | on_test | son_test | |
|---|---|---|---|---|---|
| 1 | 1 | Experimental | 24 | 61.2 | 74.8 |
| 2 | 2 | Control | 27 | 63.5 | 66.1 |
| 3 | 3 | Experimental | 22 | 58.9 | 71.3 |
| 4 | 4 | Control | 31 | 64.7 | 65.9 |
| 5 | 5 | Experimental | 26 | 60.4 | 73.2 |
Define variable types
Define each variable's type and measurement level — scale, ordinal, or nominal — in Variable View. This information helps the SAI AI assistant recommend a suitable test.
- Scale, ordinal, and nominal measurement levels
- Value labels and missing-value definitions
- The AI assistant uses this to suggest tests
| 1 | grup | Nominal |
| 2 | yas | Numeric |
| 3 | on_test | Scale |
Check normality
Before picking a test, open the Normality tab. The live panel automatically profiles every scale variable; with Shapiro-Wilk and Lilliefors-corrected Kolmogorov-Smirnov results, z-scores, and decision badges you instantly know whether to go parametric or non-parametric.
- Shapiro-Wilk (3 ≤ n ≤ 5000) and SPSS-compatible Lilliefors K-S
- Automatic Normal / Not Normal decision badges
- Histogram, Q-Q, detrended Q-Q, and boxplot charts
| Variable | S-W W | p | K-S p | z-Skewness | z-Kurtosis | Decision |
|---|---|---|---|---|---|---|
| son_test | .982 | .214 | .200 | 0.84 | -1.12 | Normal |
| motivasyon | .974 | .081 | .156 | 1.21 | -0.63 | Normal |
| kaygi | .931 | < .001 | .012 | 2.95 | 1.87 | Not Normal |
Choose your analysis
A familiar menu layout: pick the test from the Analyze menu and assign variables to the fields in the dialog. t-test, ANOVA, correlation, regression and more are a few clicks away.
- A familiar dialog layout in the Analyze menu
- Assign variables with the arrow button
- Parametric and non-parametric tests
Read the results
Results appear as tables you can move into your thesis or paper; you can choose between table formats, including APA 7. Significant values are highlighted automatically, and you can copy a table with one click.
- APA-compliant output tables
- Significance highlighting (p value)
- Confidence intervals and effect sizes included
| Statistic | t | df | p | 95% CI |
|---|---|---|---|---|
| son_test ~ grup | 4.21 | 58 | < .001 | [3.40, 9.80] |
| on_test ~ grup | 0.87 | 58 | .388 | [-1.90, 4.70] |
SPSS Syntax & R Console
Write the SPSS syntax equivalent of every analysis you run from the menus, save it, and re-run it with one click. For those who want more, the built-in R console is ready: access your data directly with R commands and write your own analysis.
- Save and re-run analyses with SPSS syntax
- Built-in R console: run R commands directly
- Switch freely between menus and code
* SPSS Syntax — Independent samples t-test. T-TEST GROUPS=grup(1 2) /VARIABLES=son_test /CRITERIA=CI(.95).
> t.test(son_test ~ grup, data = veri) t = 4.21, df = 58, p-value < 0.001 >
For the R equivalents of all analyses, see the Documentation.
Interpret with SAI
Don't drown in statistics jargon. SAI AI explains your results in plain English — what's significant, the effect size, and how to write it up in your report.
- Plain-language interpretation of results
- Suggestions for writing up your report
- Follow-up questions for deeper analysis
SAI AI interpretation is billed based on usage. See Pricing for details.
Ready? Download for free.
Download SAI Statistics and run your first analysis within minutes. Windows and Linux are supported; macOS is coming soon.
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