AI-powered statistical analysis, now on your desktop

Edit like Excel,
Analyze like SPSS —
Powered by the R language.

SAI Statistics combines ready-made statistical menus running on a real R engine with the ease of a spreadsheet. The AI assistant SAI is by your side, from choosing the right test to interpreting the results.

Download for Free How to Use

Available for Windows and Linux; macOS coming soon. No credit card required. Open source.

Try the menus, ribbon and tabs — analyses are computed in your browser.

SAI Statistics — thesis_data.savLIVE DEMO

	subject	group	gender	pretest	score
1	D001	control	Male	48	71
2	D002	experimental	Male	79	96
3	D003	control	Female	54	54
4	D004	experimental	Female	73	86
5	D005	control	Male	64	70
6	D006	experimental	Female	79	94
7	D007	control	Male	79	75
8	D008	experimental	Male	78	79
9	D009	control	Male	62	66
10	D010	experimental	Female	91	100
11	D011	control	Female	81	84
12	D012	experimental	Female	80	95
13	D013	control	Male	75	58
14	D014	experimental	Male	76	100
15	D015	control	Male	64	65
16	D016	experimental	Female	74	85
17	D017	control	Female	63	71
18	D018	experimental	Male	68	73
19	D019	control	Female	68	65
20	D020	experimental	Male	89	92
21	D021	control	Male	56	67
22	D022	experimental	Female	66	66
23	D023	control	Female	67	76
24	D024	experimental	Male	90	91
25	D025	control	Female	63	77
26	D026	experimental	Female	83	100
27	D027	control	Male	75	87
28	D028	experimental	Female	76	100
29	D029	control	Male	90	83
30	D030	experimental	Male	73	72
31	D031	control	Female	58	53
32	D032	experimental	Male	60	89
33	D033	control	Female	68	69
34	D034	experimental	Male	65	91
35	D035	control	Female	72	62
36	D036	experimental	Female	69	85
37	D037	control	Female	78	83
38	D038	experimental	Male	68	81
39	D039	control	Male	60	74
40	D040	experimental	Male	74	93
41	D041	control	Female	77	85
42	D042	experimental	Female	80	100
43	D043	control	Male	67	74
44	D044	experimental	Female	78	85
45	D045	control	Male	58	61
46	D046	experimental	Male	71	81
47	D047	control	Male	67	62
48	D048	experimental	Female	74	95
49	D049	control	Male	67	59
50	D050	experimental	Female	59	65
51	D051	control	Male	72	78
52	D052	experimental	Male	61	72
53	D053	control	Male	80	92
54	D054	experimental	Female	64	87
55	D055	control	Female	74	78
56	D056	experimental	Female	84	99
57	D057	control	Female	66	61
58	D058	experimental	Male	65	57
59	D059	control	Female	74	80
60	D060	experimental	Female	88	95
61	D061	control	Male	73	82
62	D062	experimental	Female	85	100
63	D063	control	Female	61	74
64	D064	experimental	Female	78	88
65	D065	control	Female	77	81
66	D066	experimental	Male	79	93
67	D067	control	Male	56	68
68	D068	experimental	Male	54	87
69	D069	control	Male	94	89
70	D070	experimental	Male	79	82
71	D071	control	Male	63	60
72	D072	experimental	Male	66	73
73	D073	control	Male	50	71
74	D074	experimental	Female	61	69
75	D075	control	Female	48	57
76	D076	experimental	Male	67	63
77	D077	control	Male	54	59
78	D078	experimental	Female	69	75
79	D079	control	Female	78	80
80	D080	experimental	Female	60	64
81	D081	control	Male	77	74
82	D082	experimental	Male	68	73
83	D083	control	Female	70	74
84	D084	experimental	Female	77	89
85	D085	control	Female	93	84
86	D086	experimental	Female	84	92
87	D087	control	Female	66	56
88	D088	experimental	Female	66	59
89	D089	control	Male	91	77
90	D090	experimental	Female	57	76
91	D091	control	Female	68	63
92	D092	experimental	Female	84	70
93	D093	control	Female	85	88
94	D094	experimental	Male	65	81
95	D095	control	Male	50	68
96	D096	experimental	Female	57	80
97	D097	control	Female	47	68
98	D098	experimental	Male	68	90
99	D099	control	Male	57	72
100	D100	experimental	Female	60	79
101	D101	control	Female	71	91
102	D102	experimental	Female	68	92
103	D103	control	Male	52	69
104	D104	experimental	Female	68	77
105	D105	control	Male	61	56
106	D106	experimental	Male	73	87
107	D107	control	Male	77	82
108	D108	experimental	Female	45	69
109	D109	control	Female	93	91
110	D110	experimental	Female	55	57
111	D111	control	Male	63	80
112	D112	experimental	Male	62	70
113	D113	control	Male	79	76
114	D114	experimental	Female	65	83
115	D115	control	Female	64	85
116	D116	experimental	Male	58	73
117	D117	control	Male	74	89
118	D118	experimental	Male	84	88
119	D119	control	Male	66	73
120	D120	experimental	Male	67	89
121	D121	control	Female	52	60
122	D122	experimental	Female	74	81
123	D123	control	Male	74	80
124	D124	experimental	Male	75	84
125	D125	control	Male	67	70
126	D126	experimental	Female	69	67
127	D127	control	Male	54	48
128	D128	experimental	Female	61	87

R readyPick an analysis from the menu: Analyze ▸ …

The four superpowers of statistics.

Spreadsheet ease, the accuracy of the R engine, ready-made statistics menus, and an AI assistant working alongside you.

0104

Spreadsheet-Style Data Entry

Type your data directly into the Excel-like grid, copy and paste it, or import a CSV/Excel file. Column types are detected automatically — no formulas to learn.

SAI Statistics — thesis_data.sav

	subject	group	gender	pretest	score
1	D001	control	Male	48	71
2	D002	experimental	Male	79	96
3	D003	control	Female	54	54
4	D004	experimental	Female	73	86
5	D005	control	Male	64	70

R readythesis_data.sav opened — 128 cases, 5 variables; types and value labels kept

0204

A Real R Engine

All calculations run on real R in the background. Results tested against known reference values, which you can cite with confidence in academic publications.

SAI Statistics — R

> t.test(score ~ group, data = data, var.equal = TRUE)

	Two Sample t-test

t = -5.1384, df = 126, p-value = 1.026e-06
95 percent confidence interval:
 -14.197586  -6.302414
>

R ready

0304

Ready-Made Analysis Menus

No coding — just pick from the menu. The statistical workflow you already know, with complete analysis tables and not a single line of code.

SAI Statistics — thesis_data.sav

R readyAnalyze menu: 19 groups, 60+ analyses

0404

SAI: The AI Assistant Inside the App

Type what you want in the AI Assistant panel. SAI reads your variable definitions, runs the analysis on the same R engine as the menus and adds the result to Output. It interprets any output table in one click, and the SPSS syntax or R code it suggests never runs until you approve it.

AI Assistant

Does @score differ between the experimental and control groups?

Analysis runIndependent-Samples T Test→ Output

SAI

Yes. Variances are homogeneous (Levene p = .433); the experimental group scored significantly higher on the post-test than the control group, t(126) = −5.14, p < .001. The effect size is large (d = −0.91).

Raw data rows are never sent — only variable definitions, summary statistics and result tables.

Normality Module

Stop wasting time on normality checks

Parametric or non-parametric? Choosing the right test is critical for the validity of your research. The Live Normality Panel automatically scans all scale variables and lays out Shapiro-Wilk and SPSS-compatible Lilliefors-corrected Kolmogorov-Smirnov results, skewness-kurtosis z-scores, and a 4-panel visual diagnostics view in seconds.

Live analysis: the table updates the moment your data changes
SPSS-compatible Lilliefors-corrected Kolmogorov-Smirnov
Automatic decision badges: Normal / Not Normal
Visual verification with histogram, Q-Q, detrended Q-Q, and boxplot
APA-style reporting and high-resolution chart export

Explore the normality panel

Normality — Live Panel

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

Histogram

Q-Q Plot

Detrended Q-Q

Boxplot

R readyAll scale variables are scanned automatically — with 100% data accuracy even on large datasets.

Get results in three steps.

Every step, from setup to interpretation, is designed for a researcher's pace.

01/ 03

Paste or Import Your Data

Import your Excel, CSV, or SPSS file, or paste the cells directly. Column types and missing data are flagged automatically.

SAI Statistics — Data

	score	group	age
1	78	experimental	24
2	82	control	26
3	91	experimental	23
4	69	control	29

R readyPaste complete

02/ 03

Pick Your Test

Choose your test from the Analyze menu: t-test, ANOVA, regression, correlation, non-parametric tests, and reliability analysis — one click away.

Analysis Menu

Compare Means

Independent Samples t-Testselected

Correlation Analysis

R ready

03/ 03

Interpret the Results

The tables produced by the R engine appear, and SAI explains the result in plain language and helps you draft your report.

Results — t-Test

Independent Samples Test

	t	df	p
score	4.21	126	< .001

AI interpretationSAI

The experimental group scored significantly higher.

R ready

See the Documentation for detailed walkthroughs of every test

Start analyzing today.

Download SAI Statistics for free and complete your first analysis in minutes.

Download for Free See Pricing

Edit like Excel,Analyze like SPSS —Powered by the R language.

The four superpowers of statistics.

Spreadsheet-Style Data Entry

A Real R Engine

Ready-Made Analysis Menus

SAI: The AI Assistant Inside the App

Stop wasting time on normality checks

Get results in three steps.

Paste or Import Your Data

Pick Your Test

Interpret the Results

Start analyzing today.

Edit like Excel,
Analyze like SPSS —
Powered by the R language.