Chi Square Table

For a right-tailed test at α = 0.05 with 1 degree of freedom, the critical chi-square value is 3.841. With 2 degrees of freedom the 0.05 cutoff is 5.991. Use the table or the lookup box to find other critical values. Column headings are the area to the right of the critical value.

How to read the chi-square table

A chi-square test usually asks whether a test statistic is large, so you use a right-tail column such as 0.05 or 0.01.

Find the degrees of freedom for your test (see the FAQ below if you are unsure).
Choose the significance level α, most often 0.05.
Read the cell at that row and column. That number is χ²_{α, df}.
If your test statistic is greater than the critical value, reject the null hypothesis at that α.

Example. A 2-by-2 test of independence has df = 1. At α = 0.05 the critical value is 3.841. At α = 0.01 it is 6.635. A test statistic of 5.2 would be significant at 0.05 but not at 0.01, because 5.2 is greater than 3.841 and less than 6.635.

Chi-square critical value table

Values are rounded to three decimal places. Degrees of freedom run from 1 through 30, then 40 to 100 by tens. Highlighted cells include the common 0.05 and 0.01 cutoffs at 1 df, and the 0.05 cutoff at 2 df.

Critical values of the chi-square distribution (χ²). Each column heading is the upper-tail probability α (the area to the right of the critical value). Columns 0.995 to 0.90 are the small left-side critical values used in some two-sided tests.
df	0.995	0.99	0.975	0.95	0.90	0.10	0.05	0.025	0.01	0.005	0.001
1	0.000	0.000	0.001	0.004	0.016	2.706	3.841	5.024	6.635	7.879	10.828
2	0.010	0.020	0.051	0.103	0.211	4.605	5.991	7.378	9.210	10.597	13.816
3	0.072	0.115	0.216	0.352	0.584	6.251	7.815	9.348	11.345	12.838	16.266
4	0.207	0.297	0.484	0.711	1.064	7.779	9.488	11.143	13.277	14.860	18.467
5	0.412	0.554	0.831	1.145	1.610	9.236	11.070	12.833	15.086	16.750	20.515
6	0.676	0.872	1.237	1.635	2.204	10.645	12.592	14.449	16.812	18.548	22.458
7	0.989	1.239	1.690	2.167	2.833	12.017	14.067	16.013	18.475	20.278	24.322
8	1.344	1.646	2.180	2.733	3.490	13.362	15.507	17.535	20.090	21.955	26.124
9	1.735	2.088	2.700	3.325	4.168	14.684	16.919	19.023	21.666	23.589	27.877
10	2.156	2.558	3.247	3.940	4.865	15.987	18.307	20.483	23.209	25.188	29.588
11	2.603	3.053	3.816	4.575	5.578	17.275	19.675	21.920	24.725	26.757	31.264
12	3.074	3.571	4.404	5.226	6.304	18.549	21.026	23.337	26.217	28.300	32.909
13	3.565	4.107	5.009	5.892	7.042	19.812	22.362	24.736	27.688	29.819	34.528
14	4.075	4.660	5.629	6.571	7.790	21.064	23.685	26.119	29.141	31.319	36.123
15	4.601	5.229	6.262	7.261	8.547	22.307	24.996	27.488	30.578	32.801	37.697
16	5.142	5.812	6.908	7.962	9.312	23.542	26.296	28.845	32.000	34.267	39.252
17	5.697	6.408	7.564	8.672	10.085	24.769	27.587	30.191	33.409	35.718	40.790
18	6.265	7.015	8.231	9.390	10.865	25.989	28.869	31.526	34.805	37.156	42.312
19	6.844	7.633	8.907	10.117	11.651	27.204	30.144	32.852	36.191	38.582	43.820
20	7.434	8.260	9.591	10.851	12.443	28.412	31.410	34.170	37.566	39.997	45.315
21	8.034	8.897	10.283	11.591	13.240	29.615	32.671	35.479	38.932	41.401	46.797
22	8.643	9.542	10.982	12.338	14.041	30.813	33.924	36.781	40.289	42.796	48.268
23	9.260	10.196	11.689	13.091	14.848	32.007	35.172	38.076	41.638	44.181	49.728
24	9.886	10.856	12.401	13.848	15.659	33.196	36.415	39.364	42.980	45.559	51.179
25	10.520	11.524	13.120	14.611	16.473	34.382	37.652	40.646	44.314	46.928	52.620
26	11.160	12.198	13.844	15.379	17.292	35.563	38.885	41.923	45.642	48.290	54.052
27	11.808	12.879	14.573	16.151	18.114	36.741	40.113	43.195	46.963	49.645	55.476
28	12.461	13.565	15.308	16.928	18.939	37.916	41.337	44.461	48.278	50.993	56.892
29	13.121	14.256	16.047	17.708	19.768	39.087	42.557	45.722	49.588	52.336	58.301
30	13.787	14.953	16.791	18.493	20.599	40.256	43.773	46.979	50.892	53.672	59.703
40	20.707	22.164	24.433	26.509	29.051	51.805	55.758	59.342	63.691	66.766	73.402
50	27.991	29.707	32.357	34.764	37.689	63.167	67.505	71.420	76.154	79.490	86.661
60	35.534	37.485	40.482	43.188	46.459	74.397	79.082	83.298	88.379	91.952	99.607
70	43.275	45.442	48.758	51.739	55.329	85.527	90.531	95.023	100.425	104.215	112.317
80	51.172	53.540	57.153	60.391	64.278	96.578	101.879	106.629	112.329	116.321	124.839
90	59.196	61.754	65.647	69.126	73.291	107.565	113.145	118.136	124.116	128.299	137.208
100	67.328	70.065	74.222	77.929	82.358	118.498	124.342	129.561	135.807	140.169	149.449

What is a chi-square table used for?

The χ² distribution is a right-skewed family of curves, one for each degrees of freedom, that appears when you square and add standard normal variables. In practice the table is used to look up cutoffs for:

goodness-of-fit tests (do observed counts match an expected distribution?),
tests of independence or homogeneity in contingency tables,
tests and confidence intervals for a population variance or standard deviation.

This page is a lookup table. To compute a critical value for a df or α that is not listed, use the critical chi-square value calculator.

Related tools

Chi-square table FAQ

What is a chi-square table?

A chi-square table lists critical values of the χ² distribution. You look up degrees of freedom and a right-tail probability α to get the cutoff used in a chi-square test of independence, a goodness-of-fit test, or a test about a variance.

How do I find a critical chi-square value?

Find the row for your degrees of freedom and the column for your significance level α. The cell is the critical value. If the test statistic is larger than that value, you reject the null hypothesis at that α (for the usual right-tailed chi-square test).

What is the critical value for α = 0.05 and 1 degree of freedom?

It is 3.841. That is the usual 5% cutoff for a 2-by-2 test of independence (df = (2−1)(2−1) = 1) and for a goodness-of-fit test with two categories.

Are these values left-tailed or right-tailed?

Column headings are the area to the right of the critical value. For a typical goodness-of-fit or independence test you use a right-tailed column such as 0.05 or 0.01. Columns from 0.995 to 0.90 are the small lower-tail critical values, which appear in some two-sided variance tests.

How are degrees of freedom determined?

For a goodness-of-fit test, df = k − 1 (and subtract any estimated parameters). For a test of independence in an r-by-c table, df = (r − 1)(c − 1). For a test about a single variance, df = n − 1.

What if my degrees of freedom are not in the table?

The table lists df 1 through 30, then 40, 50, 60, 70, 80, 90, and 100. For a value in between, you can use the next smaller df as a conservative critical value, or use the critical chi-square value calculator for the exact figure.