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Cross-tab and chi-square test calculator with weights, Cramér's V and Fisher's exact test (free)

Turn raw survey answers into a cross-tabulation with row, column and total percentages, then test it: Pearson chi-square, likelihood-ratio G², Cramér's V, adjusted residuals, Fisher's exact test for 2 × 2, and a design-effect correction for weighted data. Matches scipy.

Keep it one tap away for everyday use.

Your survey
Pick 2 items
Cross-tab
χ² test

Nothing is uploadedWorks offline once open

Your survey data

One row per respondent, one column per question, with a header row. The sample is a made-up survey of 240 people.

id,age_group,region,main_transport,weight
1,35-54,Urban,Walk or cycle,1.373
2,35-54,Urban,Car,0.506
3,55+,Rural,Walk or cycle,1.221
4,18-34,Rural,Car,2.015
5,55+,Rural,Car,1.38
6,35-54,Urban,,1.166
7,18-34,Urban,Bus or train,1.296
8,18-34,Rural,Walk or cycle,2.03
9,35-54,Rural,Car,2.323
10,55+,Urban,Car,0.937
11,18-34,Rural,Car,1.685
12,18-34,Rural,Bus or train,2.22
13,35-54,Urban,Car,0.846
14,18-34,Rural,Bus or train,2.4
15,35-54,Urban,Bus or train,0.617
16,55+,Rural,Car,1.174
17,18-34,Urban,Bus or train,0.63
18,35-54,Urban,Walk or cycle,1.516
19,55+,Urban,Car,0.947
20,55+,Urban,Walk or cycle,0.53
21,35-54,Urban,Car,0.745
22,18-34,Rural,Bus or train,2.705
23,55+,Rural,Car,2.102
24,35-54,Urban,Walk or cycle,1.314
25,55+,Urban,Walk or cycle,0.974
26,18-34,Urban,Car,1.456
27,35-54,Urban,Bus or train,1.166
28,55+,Urban,Car,0.505
29,18-34,Urban,Walk or cycle,1.424
30,18-34,Rural,Bus or train,0.826
31,18-34,Urban,Walk or cycle,0.996
32,35-54,Urban,Bus or train,0.631
33,35-54,Urban,Bus or train,1.486
34,18-34,Rural,Walk or cycle,2.462
35,35-54,Urban,Walk or cycle,0.677
36,18-34,Rural,Bus or train,0.979
37,35-54,Urban,Car,1.069
38,35-54,Urban,Car,0.73
39,35-54,Rural,Bus or train,2.214
40,55+,Urban,Car,1.132
41,35-54,Urban,Bus or train,1.331
42,35-54,Urban,Walk or cycle,0.727
43,18-34,Rural,Bus or train,1.014
44,35-54,Rural,Walk or cycle,1.801
45,18-34,Urban,Car,0.422
46,18-34,Urban,Bus or train,0.939
47,35-54,Urban,Walk or cycle,1.422
48,18-34,Urban,Car,1.588
49,35-54,Rural,Car,2.19
50,18-34,Urban,Car,1.102
51,18-34,Rural,Car,0.757
52,35-54,Urban,Bus or train,1.269
53,18-34,Urban,Bus or train,0.519
54,35-54,Urban,Car,0.927
55,55+,Urban,Car,1.333
56,18-34,Urban,Walk or cycle,0.421
57,55+,Urban,Walk or cycle,0.586
58,55+,Urban,Bus or train,1.215
59,35-54,Urban,Walk or cycle,1.368
60,55+,Urban,Car,0.714
61,55+,Urban,Car,0.918
62,35-54,Urban,Bus or train,1.357
63,18-34,Urban,Bus or train,1.16
64,18-34,Rural,Car,2.334
65,18-34,Rural,Car,1.789
66,35-54,Urban,Bus or train,0.629
67,18-34,Rural,Bus or train,2.469
68,55+,Urban,Walk or cycle,1.401
69,35-54,Urban,Car,0.626
70,55+,Urban,Car,1.443
71,35-54,Urban,Car,1.05
72,35-54,Rural,Car,1.419
73,18-34,Urban,Car,0.672
74,18-34,Urban,Car,0.537
75,35-54,Urban,Car,0.689
76,35-54,Rural,Walk or cycle,1.367
77,35-54,Urban,Bus or train,0.483
78,35-54,Urban,,0.428
79,18-34,Rural,Bus or train,1.754
80,18-34,Rural,Bus or train,1.35
81,35-54,Rural,Car,1.62
82,55+,Rural,Walk or cycle,2.327
83,35-54,Urban,Walk or cycle,1.091
84,18-34,Rural,Bus or train,2.781
85,35-54,Rural,Walk or cycle,2.486
86,55+,Rural,Walk or cycle,0.73
87,18-34,Urban,Walk or cycle,1.354
88,55+,Urban,Walk or cycle,0.997
89,18-34,Urban,Car,0.895
90,35-54,Urban,Walk or cycle,1.493
91,35-54,Urban,Walk or cycle,1.364
92,18-34,Urban,Walk or cycle,1.529
93,35-54,Urban,Walk or cycle,0.806
94,35-54,Urban,Car,1.12
95,18-34,Urban,Bus or train,1.085
96,18-34,Rural,Bus or train,2.742
97,18-34,Urban,Bus or train,1.011
98,18-34,Rural,Walk or cycle,0.736
99,55+,Urban,Bus or train,1.169
100,35-54,Urban,Bus or train,0.918
101,55+,Urban,Car,1.093
102,18-34,Urban,Walk or cycle,0.505
103,35-54,Rural,Bus or train,1.387
104,35-54,Rural,Car,1.833
105,35-54,Rural,Car,1.413
106,18-34,Rural,Walk or cycle,0.909
107,55+,Rural,Walk or cycle,2.341
108,35-54,Rural,Bus or train,2.406
109,35-54,Rural,Car,2.244
110,18-34,Urban,Bus or train,1.128
111,55+,Rural,Car,2.547
112,18-34,Rural,Bus or train,1.844
113,18-34,Rural,Car,0.912
114,18-34,Rural,Bus or train,2.065
115,18-34,Urban,Car,1.221
116,35-54,Urban,Car,0.67
117,18-34,Urban,Bus or train,1.172
118,18-34,Urban,Bus or train,0.411
119,18-34,Urban,Bus or train,0.687
120,35-54,Urban,Car,0.896
121,18-34,Urban,Bus or train,1.079
122,55+,Rural,Car,0.936
123,18-34,Rural,Bus or train,2.323
124,35-54,Urban,Car,0.671
125,18-34,Urban,Walk or cycle,0.997
126,35-54,Rural,Bus or train,0.835
127,35-54,Rural,Bus or train,1.116
128,55+,Urban,Car,1.319
129,35-54,Urban,Walk or cycle,1.14
130,55+,Rural,Walk or cycle,0.744
131,35-54,Urban,Walk or cycle,1.388
132,55+,Urban,Car,0.928
133,35-54,Rural,Car,1.235
134,18-34,Rural,Car,1.947
135,35-54,Rural,Car,2.429
136,35-54,Urban,Walk or cycle,1.578
137,35-54,Urban,Car,0.985
138,18-34,Urban,Walk or cycle,1.246
139,35-54,Urban,Bus or train,1.438
140,35-54,Rural,Walk or cycle,1.608
141,35-54,Urban,Walk or cycle,1.343
142,35-54,Urban,Bus or train,0.485
143,18-34,Urban,Walk or cycle,0.488
144,35-54,Urban,Car,1.002
145,35-54,Rural,Bus or train,2.782
146,35-54,Urban,Bus or train,1.297
147,35-54,Urban,Bus or train,0.71
148,18-34,Rural,Bus or train,1.708
149,55+,Urban,Car,1.23
150,18-34,Rural,Bus or train,2.678
151,18-34,Urban,Car,1.113
152,18-34,Rural,Bus or train,0.793
153,18-34,Rural,Car,1.368
154,18-34,Urban,Walk or cycle,1.321
155,18-34,Urban,Bus or train,1.065
156,35-54,Rural,Walk or cycle,1.193
157,55+,Urban,Car,1.235
158,35-54,Rural,Bus or train,0.801
159,18-34,Urban,Walk or cycle,1.584
160,35-54,Rural,Walk or cycle,1.742
161,55+,Rural,Walk or cycle,1.134
162,35-54,Rural,Car,1.226
163,18-34,Urban,Car,1.465
164,55+,Rural,Car,0.862
165,55+,Urban,Bus or train,1.375
166,18-34,Urban,Walk or cycle,1.297
167,18-34,Urban,Bus or train,0.597
168,35-54,Urban,Walk or cycle,0.742
169,35-54,Rural,Car,0.817
170,55+,Urban,Walk or cycle,1.306
171,55+,Urban,Car,1.189
172,55+,Rural,Car,2.286
173,55+,Rural,Bus or train,1.379
174,55+,Rural,Car,1.01
175,35-54,Rural,Bus or train,2.076
176,55+,Rural,Walk or cycle,1.359
177,18-34,Urban,Bus or train,1.134
178,35-54,Urban,Bus or train,0.687
179,35-54,Urban,Car,1.521
180,18-34,Rural,Bus or train,1.266
181,35-54,Rural,Bus or train,2.409
182,35-54,Urban,Bus or train,1.341
183,35-54,Rural,Car,2.277
184,55+,Rural,Bus or train,2.494
185,35-54,Urban,Walk or cycle,0.978
186,35-54,Rural,Car,1.095
187,35-54,Urban,Bus or train,1.074
188,18-34,Rural,Car,0.708
189,35-54,Urban,Car,1.273
190,18-34,Rural,Bus or train,1.5
191,35-54,Rural,Car,2.59
192,18-34,Urban,Walk or cycle,1.437
193,18-34,Urban,Bus or train,0.507
194,35-54,Urban,Walk or cycle,0.715
195,18-34,Rural,Walk or cycle,0.874
196,35-54,Urban,Car,0.839
197,55+,Rural,Walk or cycle,1.803
198,18-34,Urban,Bus or train,0.987
199,35-54,Urban,Car,0.838
200,18-34,Rural,Bus or train,1.641
201,55+,Urban,Walk or cycle,1.531
202,35-54,Urban,Walk or cycle,1.282
203,35-54,Rural,Car,2.629
204,55+,Urban,Car,1.05
205,35-54,Urban,Bus or train,1.476
206,18-34,Urban,Walk or cycle,0.683
207,55+,Urban,Walk or cycle,1.479
208,35-54,Urban,Walk or cycle,0.879
209,18-34,Urban,Bus or train,0.903
210,18-34,Rural,Bus or train,1.986
211,18-34,Rural,Bus or train,2.581
212,18-34,Rural,Car,1.775
213,18-34,Rural,Bus or train,2.514
214,35-54,Urban,Walk or cycle,0.599
215,55+,Rural,Car,2.25
216,18-34,Urban,Bus or train,0.46
217,35-54,Rural,Bus or train,1.774
218,35-54,Rural,Walk or cycle,1.217
219,35-54,Urban,Car,1.151
220,18-34,Urban,Bus or train,0.676
221,55+,Urban,Car,1.299
222,35-54,Rural,Car,1.987
223,55+,Urban,Walk or cycle,1.407
224,55+,Urban,Car,0.41
225,35-54,Urban,Car,0.438
226,18-34,Rural,Car,2.624
227,35-54,Urban,Car,1.417
228,35-54,Rural,Bus or train,2.633
229,35-54,Rural,Car,1.67
230,35-54,Rural,Bus or train,1.783
231,18-34,Rural,Walk or cycle,2.743
232,35-54,Rural,Car,2.682
233,35-54,Urban,Walk or cycle,1.219
234,35-54,Urban,Bus or train,1.18
235,18-34,Urban,Walk or cycle,0.938
236,55+,Rural,Car,2.797
237,18-34,Rural,Walk or cycle,1.124
238,35-54,Urban,Bus or train,0.694
239,55+,Urban,Bus or train,1.405
240,55+,Urban,Walk or cycle,1.073

Rows Columns Weight

Rows with a blank answer in either question (or a blank weight) are left out and counted. A weight column makes each person count for their weight, as survey weights do.

What it does

A cross-tabulation shows how the answers to one survey question are spread across the answers to another: for example, how people of different ages travel to work. This tool builds the table from your raw data (one row per respondent) and tests whether the two questions are related:

Counts and percentages: row %, column % or total %, with totals.
Pearson chi-square and the likelihood-ratio G² test of independence, with degrees of freedom and p-values.
Cramér’s V, the strength of the relationship from 0 (none) to 1.
Adjusted standardised residuals for every cell, marked when beyond ±1.96, so you can see which combinations are more or less common than chance.
For 2 × 2 tables: Yates’ continuity correction, Fisher’s exact test and the odds ratio.
Survey weights: weighted counts and percentages, and a chi-square corrected for the design effect of the weights.

It works well with the sample size and power calculator, the reliability and agreement and the CSV profiler and SQL playground.

How to use it

Paste your data or open a CSV or Excel file: one row per respondent, one column per question, with a header row.
Choose the question for the rows and the one for the columns. Columns with 2 to 50 different answers are offered.
If your data has a weight column, choose it under Weight.
Switch between row %, column %, total % and counts only. Download the table as CSV, or the full report as an image, PDF or Word file.

Rows with a blank answer in either question are left out and the tool says how many.

Weighted data, explained

With weights, simply running the chi-square on the weighted counts is wrong: the weighted total is not the number of people asked, and unequal weights make estimates less precise. This tool uses a simple, clearly stated correction in the spirit of Rao and Scott’s first-order adjustment. It computes the chi-square from the weighted shares as if they came from the actual number of respondents, then divides it by Kish’s design effect of the weights, deff = n Σw² / (Σw)². This handles unequal weights only. If your survey also has clusters or strata, use survey software with the full Rao-Scott correction.

Worked example (made-up data)

The sample is a made-up survey of 240 people: age group, region, main way of getting to work and a weight. Two people did not answer the transport question, so 238 are used. Age group by transport gives Pearson χ² = 22.455 with 4 degrees of freedom, p = 0.0002, G² = 24.223, and Cramér’s V = 0.217. The residuals show that people aged 18 to 34 use the bus or train more than expected (adjusted residual +3.91) and those 55 and over use it less (−3.79).

With the weight column, the design effect is 1.208 (an effective sample of about 197), and the design-adjusted χ² is 19.205, p = 0.0007.

For a 2 × 2 table such as [[3, 1], [1, 3]], Fisher’s exact two-sided p is 0.486 and the odds ratio 9.

How it was checked

Counts, expected counts, Pearson χ² (with and without Yates’ correction), G², Cramér’s V and Fisher’s exact test (two-sided and one-sided, and the odds ratio) agree with scipy, and the Pearson and adjusted residuals with statsmodels, to at least nine significant figures. The weighted correction matches an independent numpy calculation.

Frequently asked questions

When should I use Fisher’s exact test? When any expected count in a 2 × 2 table is below 5; the tool warns you. For bigger tables with small cells, merge categories.

What is a big Cramér’s V? It depends on the table size. The tool labels it negligible, small, medium or large using Cohen’s guidelines adjusted for the number of categories.

Is my survey data uploaded? No. Everything runs in your browser and works offline.

Where the numbers come from

Formulas: Pearson (1900), the likelihood-ratio G² test, Cramér (1946), Haberman (1973) adjusted residuals, Fisher (1922) exact test, Yates (1934) correction, Kish (1965) design effect for weights, and the first-order idea of Rao and Scott (1981). Example data made up.

Standard scientific values, such as constants, atomic weights and melting points, are facts found in every textbook; we name where ours were checked. If you are an author or publisher and want a value, a credit or a table changed or removed, tell us and we will act quickly.

Last updated 2026-11-09.

Cross-tab and chi-square test calculator with weights, Cramér's V and Fisher's exact test (free)

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Your survey data

Table

Adjusted standardised residuals