Statistical Tables

The field of statistics relies heavily on mathematical formulas and calculations to make sense of data. Statistical tables, such as the z-table, t-table, f-table, and Pearson table, are essential tools for statisticians and researchers. These tables provide critical values for different probability distributions, enabling users to perform statistical tests, calculate confidence intervals, and make informed decisions based on data analysis.

To interpret the table containing z-values from 0.00 to 4.00 and their corresponding one-tailed and two-tailed probabilities, follow these steps:

Identify the type of test: Determine whether you are conducting a one-tailed or two-tailed test. A one-tailed test is used when the direction of the relationship is hypothesized, while a two-tailed test is used when no specific direction is hypothesized.
Locate the z-value: Calculate the z-value (z) for your data. This is typically obtained through hypothesis testing, such as the z-test or as part of the output of other tests like linear regression.
Find the probabilities: In the table, locate the row with the z-value closest to the calculated z-value from your data. In that row, you will find the one-tailed and two-tailed probabilities associated with that z-value.

For one-tailed tests:

The one-tailed probability represents the probability of observing a value as extreme as the calculated z-value or more extreme in the specified direction, given that the null hypothesis is true.

For two-tailed tests:

The two-tailed probability represents the probability of observing a value as extreme as the calculated z-value or more extreme in either direction, given that the null hypothesis is true.

Compare the probabilities with the desired significance level (α): The significance level, denoted as α, is the probability of rejecting the null hypothesis when it is true. Commonly used significance levels are 0.05 and 0.01. If the probability from the table is less than or equal to your chosen α, you can reject the null hypothesis, suggesting that there is a significant effect or relationship between the variables under consideration. If the probability is greater than α, you fail to reject the null hypothesis, meaning that there is not enough evidence to suggest a significant effect or relationship between the variables.

The values under the one and two-tailed columns represent the area between the Mean and Z (in percent) in the normal distribution.

Probabilities for z-values from 0.00 to 4.00
z_value	one_tailed_probability	two_tailed_probability
0.00	0.5000	1.0000
0.01	0.4960	0.9920
0.02	0.4920	0.9840
0.03	0.4880	0.9761
0.04	0.4840	0.9681
0.05	0.4801	0.9601
0.06	0.4761	0.9522
0.07	0.4721	0.9442
0.08	0.4681	0.9362
0.09	0.4641	0.9283
0.10	0.4602	0.9203
0.11	0.4562	0.9124
0.12	0.4522	0.9045
0.13	0.4483	0.8966
0.14	0.4443	0.8887
0.15	0.4404	0.8808
0.16	0.4364	0.8729
0.17	0.4325	0.8650
0.18	0.4286	0.8572
0.19	0.4247	0.8493
0.20	0.4207	0.8415
0.21	0.4168	0.8337
0.22	0.4129	0.8259
0.23	0.4090	0.8181
0.24	0.4052	0.8103
0.25	0.4013	0.8026
0.26	0.3974	0.7949
0.27	0.3936	0.7872
0.28	0.3897	0.7795
0.29	0.3859	0.7718
0.30	0.3821	0.7642
0.31	0.3783	0.7566
0.32	0.3745	0.7490
0.33	0.3707	0.7414
0.34	0.3669	0.7339
0.35	0.3632	0.7263
0.36	0.3594	0.7188
0.37	0.3557	0.7114
0.38	0.3520	0.7039
0.39	0.3483	0.6965
0.40	0.3446	0.6892
0.41	0.3409	0.6818
0.42	0.3372	0.6745
0.43	0.3336	0.6672
0.44	0.3300	0.6599
0.45	0.3264	0.6527
0.46	0.3228	0.6455
0.47	0.3192	0.6384
0.48	0.3156	0.6312
0.49	0.3121	0.6241
0.50	0.3085	0.6171
0.51	0.3050	0.6101
0.52	0.3015	0.6031
0.53	0.2981	0.5961
0.54	0.2946	0.5892
0.55	0.2912	0.5823
0.56	0.2877	0.5755
0.57	0.2843	0.5687
0.58	0.2810	0.5619
0.59	0.2776	0.5552
0.60	0.2743	0.5485
0.61	0.2709	0.5419
0.62	0.2676	0.5353
0.63	0.2643	0.5287
0.64	0.2611	0.5222
0.65	0.2578	0.5157
0.66	0.2546	0.5093
0.67	0.2514	0.5029
0.68	0.2483	0.4965
0.69	0.2451	0.4902
0.70	0.2420	0.4839
0.71	0.2389	0.4777
0.72	0.2358	0.4715
0.73	0.2327	0.4654
0.74	0.2296	0.4593
0.75	0.2266	0.4533
0.76	0.2236	0.4473
0.77	0.2206	0.4413
0.78	0.2177	0.4354
0.79	0.2148	0.4295
0.80	0.2119	0.4237
0.81	0.2090	0.4179
0.82	0.2061	0.4122
0.83	0.2033	0.4065
0.84	0.2005	0.4009
0.85	0.1977	0.3953
0.86	0.1949	0.3898
0.87	0.1922	0.3843
0.88	0.1894	0.3789
0.89	0.1867	0.3735
0.90	0.1841	0.3681
0.91	0.1814	0.3628
0.92	0.1788	0.3576
0.93	0.1762	0.3524
0.94	0.1736	0.3472
0.95	0.1711	0.3421
0.96	0.1685	0.3371
0.97	0.1660	0.3320
0.98	0.1635	0.3271
0.99	0.1611	0.3222
1.00	0.1587	0.3173
1.01	0.1562	0.3125
1.02	0.1539	0.3077
1.03	0.1515	0.3030
1.04	0.1492	0.2983
1.05	0.1469	0.2937
1.06	0.1446	0.2891
1.07	0.1423	0.2846
1.08	0.1401	0.2801
1.09	0.1379	0.2757
1.10	0.1357	0.2713
1.11	0.1335	0.2670
1.12	0.1314	0.2627
1.13	0.1292	0.2585
1.14	0.1271	0.2543
1.15	0.1251	0.2501
1.16	0.1230	0.2460
1.17	0.1210	0.2420
1.18	0.1190	0.2380
1.19	0.1170	0.2340
1.20	0.1151	0.2301
1.21	0.1131	0.2263
1.22	0.1112	0.2225
1.23	0.1093	0.2187
1.24	0.1075	0.2150
1.25	0.1056	0.2113
1.26	0.1038	0.2077
1.27	0.1020	0.2041
1.28	0.1003	0.2005
1.29	0.0985	0.1971
1.30	0.0968	0.1936
1.31	0.0951	0.1902
1.32	0.0934	0.1868
1.33	0.0918	0.1835
1.34	0.0901	0.1802
1.35	0.0885	0.1770
1.36	0.0869	0.1738
1.37	0.0853	0.1707
1.38	0.0838	0.1676
1.39	0.0823	0.1645
1.40	0.0808	0.1615
1.41	0.0793	0.1585
1.42	0.0778	0.1556
1.43	0.0764	0.1527
1.44	0.0749	0.1499
1.45	0.0735	0.1471
1.46	0.0721	0.1443
1.47	0.0708	0.1416
1.48	0.0694	0.1389
1.49	0.0681	0.1362
1.50	0.0668	0.1336
1.51	0.0655	0.1310
1.52	0.0643	0.1285
1.53	0.0630	0.1260
1.54	0.0618	0.1236
1.55	0.0606	0.1211
1.56	0.0594	0.1188
1.57	0.0582	0.1164
1.58	0.0571	0.1141
1.59	0.0559	0.1118
1.60	0.0548	0.1096
1.61	0.0537	0.1074
1.62	0.0526	0.1052
1.63	0.0516	0.1031
1.64	0.0505	0.1010
1.65	0.0495	0.0989
1.66	0.0485	0.0969
1.67	0.0475	0.0949
1.68	0.0465	0.0930
1.69	0.0455	0.0910
1.70	0.0446	0.0891
1.71	0.0436	0.0873
1.72	0.0427	0.0854
1.73	0.0418	0.0836
1.74	0.0409	0.0819
1.75	0.0401	0.0801
1.76	0.0392	0.0784
1.77	0.0384	0.0767
1.78	0.0375	0.0751
1.79	0.0367	0.0735
1.80	0.0359	0.0719
1.81	0.0351	0.0703
1.82	0.0344	0.0688
1.83	0.0336	0.0672
1.84	0.0329	0.0658
1.85	0.0322	0.0643
1.86	0.0314	0.0629
1.87	0.0307	0.0615
1.88	0.0301	0.0601
1.89	0.0294	0.0588
1.90	0.0287	0.0574
1.91	0.0281	0.0561
1.92	0.0274	0.0549
1.93	0.0268	0.0536
1.94	0.0262	0.0524
1.95	0.0256	0.0512
1.96	0.0250	0.0500
1.97	0.0244	0.0488
1.98	0.0239	0.0477
1.99	0.0233	0.0466
2.00	0.0228	0.0455
2.01	0.0222	0.0444
2.02	0.0217	0.0434
2.03	0.0212	0.0424
2.04	0.0207	0.0414
2.05	0.0202	0.0404
2.06	0.0197	0.0394
2.07	0.0192	0.0385
2.08	0.0188	0.0375
2.09	0.0183	0.0366
2.10	0.0179	0.0357
2.11	0.0174	0.0349
2.12	0.0170	0.0340
2.13	0.0166	0.0332
2.14	0.0162	0.0324
2.15	0.0158	0.0316
2.16	0.0154	0.0308
2.17	0.0150	0.0300
2.18	0.0146	0.0293
2.19	0.0143	0.0285
2.20	0.0139	0.0278
2.21	0.0136	0.0271
2.22	0.0132	0.0264
2.23	0.0129	0.0257
2.24	0.0125	0.0251
2.25	0.0122	0.0244
2.26	0.0119	0.0238
2.27	0.0116	0.0232
2.28	0.0113	0.0226
2.29	0.0110	0.0220
2.30	0.0107	0.0214
2.31	0.0104	0.0209
2.32	0.0102	0.0203
2.33	0.0099	0.0198
2.34	0.0096	0.0193
2.35	0.0094	0.0188
2.36	0.0091	0.0183
2.37	0.0089	0.0178
2.38	0.0087	0.0173
2.39	0.0084	0.0168
2.40	0.0082	0.0164
2.41	0.0080	0.0160
2.42	0.0078	0.0155
2.43	0.0075	0.0151
2.44	0.0073	0.0147
2.45	0.0071	0.0143
2.46	0.0069	0.0139
2.47	0.0068	0.0135
2.48	0.0066	0.0131
2.49	0.0064	0.0128
2.50	0.0062	0.0124
2.51	0.0060	0.0121
2.52	0.0059	0.0117
2.53	0.0057	0.0114
2.54	0.0055	0.0111
2.55	0.0054	0.0108
2.56	0.0052	0.0105
2.57	0.0051	0.0102
2.58	0.0049	0.0099
2.59	0.0048	0.0096
2.60	0.0047	0.0093
2.61	0.0045	0.0091
2.62	0.0044	0.0088
2.63	0.0043	0.0085
2.64	0.0041	0.0083
2.65	0.0040	0.0080
2.66	0.0039	0.0078
2.67	0.0038	0.0076
2.68	0.0037	0.0074
2.69	0.0036	0.0071
2.70	0.0035	0.0069
2.71	0.0034	0.0067
2.72	0.0033	0.0065
2.73	0.0032	0.0063
2.74	0.0031	0.0061
2.75	0.0030	0.0060
2.76	0.0029	0.0058
2.77	0.0028	0.0056
2.78	0.0027	0.0054
2.79	0.0026	0.0053
2.80	0.0026	0.0051
2.81	0.0025	0.0050
2.82	0.0024	0.0048
2.83	0.0023	0.0047
2.84	0.0023	0.0045
2.85	0.0022	0.0044
2.86	0.0021	0.0042
2.87	0.0021	0.0041
2.88	0.0020	0.0040
2.89	0.0019	0.0039
2.90	0.0019	0.0037
2.91	0.0018	0.0036
2.92	0.0018	0.0035
2.93	0.0017	0.0034
2.94	0.0016	0.0033
2.95	0.0016	0.0032
2.96	0.0015	0.0031
2.97	0.0015	0.0030
2.98	0.0014	0.0029
2.99	0.0014	0.0028
3.00	0.0013	0.0027
3.01	0.0013	0.0026
3.02	0.0013	0.0025
3.03	0.0012	0.0024
3.04	0.0012	0.0024
3.05	0.0011	0.0023
3.06	0.0011	0.0022
3.07	0.0011	0.0021
3.08	0.0010	0.0021
3.09	0.0010	0.0020
3.10	0.0010	0.0019
3.11	0.0009	0.0019
3.12	0.0009	0.0018
3.13	0.0009	0.0017
3.14	0.0008	0.0017
3.15	0.0008	0.0016
3.16	0.0008	0.0016
3.17	0.0008	0.0015
3.18	0.0007	0.0015
3.19	0.0007	0.0014
3.20	0.0007	0.0014
3.21	0.0007	0.0013
3.22	0.0006	0.0013
3.23	0.0006	0.0012
3.24	0.0006	0.0012
3.25	0.0006	0.0012
3.26	0.0006	0.0011
3.27	0.0005	0.0011
3.28	0.0005	0.0010
3.29	0.0005	0.0010
3.30	0.0005	0.0010
3.31	0.0005	0.0009
3.32	0.0005	0.0009
3.33	0.0004	0.0009
3.34	0.0004	0.0008
3.35	0.0004	0.0008
3.36	0.0004	0.0008
3.37	0.0004	0.0008
3.38	0.0004	0.0007
3.39	0.0003	0.0007
3.40	0.0003	0.0007
3.41	0.0003	0.0006
3.42	0.0003	0.0006
3.43	0.0003	0.0006
3.44	0.0003	0.0006
3.45	0.0003	0.0006
3.46	0.0003	0.0005
3.47	0.0003	0.0005
3.48	0.0003	0.0005
3.49	0.0002	0.0005
3.50	0.0002	0.0005
3.51	0.0002	0.0004
3.52	0.0002	0.0004
3.53	0.0002	0.0004
3.54	0.0002	0.0004
3.55	0.0002	0.0004
3.56	0.0002	0.0004
3.57	0.0002	0.0004
3.58	0.0002	0.0003
3.59	0.0002	0.0003
3.60	0.0002	0.0003
3.61	0.0002	0.0003
3.62	0.0001	0.0003
3.63	0.0001	0.0003
3.64	0.0001	0.0003
3.65	0.0001	0.0003
3.66	0.0001	0.0003
3.67	0.0001	0.0002
3.68	0.0001	0.0002
3.69	0.0001	0.0002
3.70	0.0001	0.0002
3.71	0.0001	0.0002
3.72	0.0001	0.0002
3.73	0.0001	0.0002
3.74	0.0001	0.0002
3.75	0.0001	0.0002
3.76	0.0001	0.0002
3.77	0.0001	0.0002
3.78	0.0001	0.0002
3.79	0.0001	0.0002
3.80	0.0001	0.0001
3.81	0.0001	0.0001
3.82	0.0001	0.0001
3.83	0.0001	0.0001
3.84	0.0001	0.0001
3.85	0.0001	0.0001
3.86	0.0001	0.0001
3.87	0.0001	0.0001
3.88	0.0001	0.0001
3.89	0.0001	0.0001
3.90	0.0000	0.0001
3.91	0.0000	0.0001
3.92	0.0000	0.0001
3.93	0.0000	0.0001
3.94	0.0000	0.0001
3.95	0.0000	0.0001
3.96	0.0000	0.0001
3.97	0.0000	0.0001
3.98	0.0000	0.0001
3.99	0.0000	0.0001
4.00	0.0000	0.0001

t-table distribution for two-tailed test
df	alpha	tcritical
1	0.050	12.706
1	0.010	9.925
1	0.001	12.924
2	0.050	2.776
2	0.010	4.032
2	0.001	5.959
3	0.050	2.365
3	0.010	3.355
3	0.001	4.781
4	0.050	2.228
4	0.010	3.106
4	0.001	4.318
5	0.050	2.160
5	0.010	2.977
5	0.001	4.073
6	0.050	2.120
6	0.010	2.898
6	0.001	3.922
7	0.050	2.093
7	0.010	2.845
7	0.001	3.819
8	0.050	2.074
8	0.010	2.807
8	0.001	3.745
9	0.050	2.060
9	0.010	2.779
9	0.001	3.690
10	0.050	2.048
10	0.010	2.756
10	0.001	3.646
11	0.050	12.706
11	0.010	9.925
11	0.001	12.924
12	0.050	2.776
12	0.010	4.032
12	0.001	5.959
13	0.050	2.365
13	0.010	3.355
13	0.001	4.781
14	0.050	2.228
14	0.010	3.106
14	0.001	4.318
15	0.050	2.160
15	0.010	2.977
15	0.001	4.073
16	0.050	2.120
16	0.010	2.898
16	0.001	3.922
17	0.050	2.093
17	0.010	2.845
17	0.001	3.819
18	0.050	2.074
18	0.010	2.807
18	0.001	3.745
19	0.050	2.060
19	0.010	2.779
19	0.001	3.690
20	0.050	2.048
20	0.010	2.756
20	0.001	3.646
21	0.050	12.706
21	0.010	9.925
21	0.001	12.924
22	0.050	2.776
22	0.010	4.032
22	0.001	5.959
23	0.050	2.365
23	0.010	3.355
23	0.001	4.781
24	0.050	2.228
24	0.010	3.106
24	0.001	4.318
25	0.050	2.160
25	0.010	2.977
25	0.001	4.073
26	0.050	2.120
26	0.010	2.898
26	0.001	3.922
27	0.050	2.093
27	0.010	2.845
27	0.001	3.819
28	0.050	2.074
28	0.010	2.807
28	0.001	3.745
29	0.050	2.060
29	0.010	2.779
29	0.001	3.690
30	0.050	2.048
30	0.010	2.756
30	0.001	3.646

t-table distribution for one-tailed test
df	alpha	tcritical
1	0.050	6.314
1	0.010	6.965
1	0.001	10.215
2	0.050	2.132
2	0.010	3.365
2	0.001	5.208
3	0.050	1.895
3	0.010	2.896
3	0.001	4.297
4	0.050	1.812
4	0.010	2.718
4	0.001	3.930
5	0.050	1.771
5	0.010	2.624
5	0.001	3.733
6	0.050	1.746
6	0.010	2.567
6	0.001	3.610
7	0.050	1.729
7	0.010	2.528
7	0.001	3.527
8	0.050	1.717
8	0.010	2.500
8	0.001	3.467
9	0.050	1.708
9	0.010	2.479
9	0.001	3.421
10	0.050	1.701
10	0.010	2.462
10	0.001	3.385
11	0.050	6.314
11	0.010	6.965
11	0.001	10.215
12	0.050	2.132
12	0.010	3.365
12	0.001	5.208
13	0.050	1.895
13	0.010	2.896
13	0.001	4.297
14	0.050	1.812
14	0.010	2.718
14	0.001	3.930
15	0.050	1.771
15	0.010	2.624
15	0.001	3.733
16	0.050	1.746
16	0.010	2.567
16	0.001	3.610
17	0.050	1.729
17	0.010	2.528
17	0.001	3.527
18	0.050	1.717
18	0.010	2.500
18	0.001	3.467
19	0.050	1.708
19	0.010	2.479
19	0.001	3.421
20	0.050	1.701
20	0.010	2.462
20	0.001	3.385
21	0.050	6.314
21	0.010	6.965
21	0.001	10.215
22	0.050	2.132
22	0.010	3.365
22	0.001	5.208
23	0.050	1.895
23	0.010	2.896
23	0.001	4.297
24	0.050	1.812
24	0.010	2.718
24	0.001	3.930
25	0.050	1.771
25	0.010	2.624
25	0.001	3.733
26	0.050	1.746
26	0.010	2.567
26	0.001	3.610
27	0.050	1.729
27	0.010	2.528
27	0.001	3.527
28	0.050	1.717
28	0.010	2.500
28	0.001	3.467
29	0.050	1.708
29	0.010	2.479
29	0.001	3.421
30	0.050	1.701
30	0.010	2.462
30	0.001	3.385

To interpret the table containing critical values for Pearson’s correlation coefficient for both one-tailed and two-tailed tests with sample sizes ranging from 5 to 100, follow these steps:

Identify the type of test: Determine whether you are conducting a one-tailed or two-tailed test. A one-tailed test is used when the direction of the relationship is hypothesized, while a two-tailed test is used when no specific direction is hypothesized.
Choose the desired significance level (α): The significance level, denoted as α, is the probability of rejecting the null hypothesis when it is true. Commonly used significance levels are 0.05 and 0.01.
Locate the degrees of freedom (df): Degrees of freedom (df) are calculated as the sample size (n) minus 2. Find the row in the table corresponding to the df of your data.
Find the critical value: In the table, locate the critical value corresponding to the selected test type (one-tailed or two-tailed), significance level (α), and degrees of freedom (df). This critical value is the threshold at which you will reject or fail to reject the null hypothesis.
Compare the critical value with the calculated Pearson’s correlation coefficient (r): Calculate the Pearson’s correlation coefficient (r) for your data. If the absolute value of the calculated r is greater than or equal to the critical value found in the table, you can reject the null hypothesis, concluding that there is a significant relationship between the two variables. If the absolute value of the calculated r is less than the critical value, you fail to reject the null hypothesis, meaning that there is not enough evidence to suggest a significant relationship between the two variables.

Remember that rejecting or failing to reject the null hypothesis does not prove causation, but rather indicates the presence or absence of a significant correlation between the two variables.

Critical values for Pearson’s correlation coefficient
alpha	degrees_of_freedom	critical_value	test_tail
0.05	3	2.353	one-tailed
0.05	4	2.353	one-tailed
0.05	5	2.353	one-tailed
0.05	6	2.353	one-tailed
0.05	7	2.353	one-tailed
0.05	8	2.353	one-tailed
0.05	9	2.353	one-tailed
0.05	10	2.353	one-tailed
0.05	11	2.353	one-tailed
0.05	12	2.353	one-tailed
0.05	13	2.353	one-tailed
0.05	14	2.353	one-tailed
0.05	15	2.353	one-tailed
0.05	16	2.353	one-tailed
0.05	17	2.353	one-tailed
0.05	18	2.353	one-tailed
0.05	19	2.353	one-tailed
0.05	20	2.353	one-tailed
0.05	21	2.353	one-tailed
0.05	22	2.353	one-tailed
0.05	23	2.353	one-tailed
0.05	24	2.353	one-tailed
0.05	25	2.353	one-tailed
0.05	26	2.353	one-tailed
0.05	27	2.353	one-tailed
0.05	28	2.353	one-tailed
0.05	29	2.353	one-tailed
0.05	30	2.353	one-tailed
0.05	31	2.353	one-tailed
0.05	32	2.353	one-tailed
0.05	33	2.353	one-tailed
0.05	34	2.353	one-tailed
0.05	35	2.353	one-tailed
0.05	36	2.353	one-tailed
0.05	37	2.353	one-tailed
0.05	38	2.353	one-tailed
0.05	39	2.353	one-tailed
0.05	40	2.353	one-tailed
0.05	41	2.353	one-tailed
0.05	42	2.353	one-tailed
0.05	43	2.353	one-tailed
0.05	44	2.353	one-tailed
0.05	45	2.353	one-tailed
0.05	46	2.353	one-tailed
0.05	47	2.353	one-tailed
0.05	48	2.353	one-tailed
0.05	49	2.353	one-tailed
0.05	50	2.353	one-tailed
0.05	51	2.353	one-tailed
0.05	52	2.353	one-tailed
0.05	53	2.353	one-tailed
0.05	54	2.353	one-tailed
0.05	55	2.353	one-tailed
0.05	56	2.353	one-tailed
0.05	57	2.353	one-tailed
0.05	58	2.353	one-tailed
0.05	59	2.353	one-tailed
0.05	60	2.353	one-tailed
0.05	61	2.353	one-tailed
0.05	62	2.353	one-tailed
0.05	63	2.353	one-tailed
0.05	64	2.353	one-tailed
0.05	65	2.353	one-tailed
0.05	66	2.353	one-tailed
0.05	67	2.353	one-tailed
0.05	68	2.353	one-tailed
0.05	69	2.353	one-tailed
0.05	70	2.353	one-tailed
0.05	71	2.353	one-tailed
0.05	72	2.353	one-tailed
0.05	73	2.353	one-tailed
0.05	74	2.353	one-tailed
0.05	75	2.353	one-tailed
0.05	76	2.353	one-tailed
0.05	77	2.353	one-tailed
0.05	78	2.353	one-tailed
0.05	79	2.353	one-tailed
0.05	80	2.353	one-tailed
0.05	81	2.353	one-tailed
0.05	82	2.353	one-tailed
0.05	83	2.353	one-tailed
0.05	84	2.353	one-tailed
0.05	85	2.353	one-tailed
0.05	86	2.353	one-tailed
0.05	87	2.353	one-tailed
0.05	88	2.353	one-tailed
0.05	89	2.353	one-tailed
0.05	90	2.353	one-tailed
0.05	91	2.353	one-tailed
0.05	92	2.353	one-tailed
0.05	93	2.353	one-tailed
0.05	94	2.353	one-tailed
0.05	95	2.353	one-tailed
0.05	96	2.353	one-tailed
0.05	97	2.353	one-tailed
0.05	98	2.353	one-tailed
0.01	3	2.353	one-tailed
0.01	4	2.353	one-tailed
0.01	5	2.353	one-tailed
0.01	6	2.353	one-tailed
0.01	7	2.353	one-tailed
0.01	8	2.353	one-tailed
0.01	9	2.353	one-tailed
0.01	10	2.353	one-tailed
0.01	11	2.353	one-tailed
0.01	12	2.353	one-tailed
0.01	13	2.353	one-tailed
0.01	14	2.353	one-tailed
0.01	15	2.353	one-tailed
0.01	16	2.353	one-tailed
0.01	17	2.353	one-tailed
0.01	18	2.353	one-tailed
0.01	19	2.353	one-tailed
0.01	20	2.353	one-tailed
0.01	21	2.353	one-tailed
0.01	22	2.353	one-tailed
0.01	23	2.353	one-tailed
0.01	24	2.353	one-tailed
0.01	25	2.353	one-tailed
0.01	26	2.353	one-tailed
0.01	27	2.353	one-tailed
0.01	28	2.353	one-tailed
0.01	29	2.353	one-tailed
0.01	30	2.353	one-tailed
0.01	31	2.353	one-tailed
0.01	32	2.353	one-tailed
0.01	33	2.353	one-tailed
0.01	34	2.353	one-tailed
0.01	35	2.353	one-tailed
0.01	36	2.353	one-tailed
0.01	37	2.353	one-tailed
0.01	38	2.353	one-tailed
0.01	39	2.353	one-tailed
0.01	40	2.353	one-tailed
0.01	41	2.353	one-tailed
0.01	42	2.353	one-tailed
0.01	43	2.353	one-tailed
0.01	44	2.353	one-tailed
0.01	45	2.353	one-tailed
0.01	46	2.353	one-tailed
0.01	47	2.353	one-tailed
0.01	48	2.353	one-tailed
0.01	49	2.353	one-tailed
0.01	50	2.353	one-tailed
0.01	51	2.353	one-tailed
0.01	52	2.353	one-tailed
0.01	53	2.353	one-tailed
0.01	54	2.353	one-tailed
0.01	55	2.353	one-tailed
0.01	56	2.353	one-tailed
0.01	57	2.353	one-tailed
0.01	58	2.353	one-tailed
0.01	59	2.353	one-tailed
0.01	60	2.353	one-tailed
0.01	61	2.353	one-tailed
0.01	62	2.353	one-tailed
0.01	63	2.353	one-tailed
0.01	64	2.353	one-tailed
0.01	65	2.353	one-tailed
0.01	66	2.353	one-tailed
0.01	67	2.353	one-tailed
0.01	68	2.353	one-tailed
0.01	69	2.353	one-tailed
0.01	70	2.353	one-tailed
0.01	71	2.353	one-tailed
0.01	72	2.353	one-tailed
0.01	73	2.353	one-tailed
0.01	74	2.353	one-tailed
0.01	75	2.353	one-tailed
0.01	76	2.353	one-tailed
0.01	77	2.353	one-tailed
0.01	78	2.353	one-tailed
0.01	79	2.353	one-tailed
0.01	80	2.353	one-tailed
0.01	81	2.353	one-tailed
0.01	82	2.353	one-tailed
0.01	83	2.353	one-tailed
0.01	84	2.353	one-tailed
0.01	85	2.353	one-tailed
0.01	86	2.353	one-tailed
0.01	87	2.353	one-tailed
0.01	88	2.353	one-tailed
0.01	89	2.353	one-tailed
0.01	90	2.353	one-tailed
0.01	91	2.353	one-tailed
0.01	92	2.353	one-tailed
0.01	93	2.353	one-tailed
0.01	94	2.353	one-tailed
0.01	95	2.353	one-tailed
0.01	96	2.353	one-tailed
0.01	97	2.353	one-tailed
0.01	98	2.353	one-tailed
0.05	3	3.182	two-tailed
0.05	4	3.182	two-tailed
0.05	5	3.182	two-tailed
0.05	6	3.182	two-tailed
0.05	7	3.182	two-tailed
0.05	8	3.182	two-tailed
0.05	9	3.182	two-tailed
0.05	10	3.182	two-tailed
0.05	11	3.182	two-tailed
0.05	12	3.182	two-tailed
0.05	13	3.182	two-tailed
0.05	14	3.182	two-tailed
0.05	15	3.182	two-tailed
0.05	16	3.182	two-tailed
0.05	17	3.182	two-tailed
0.05	18	3.182	two-tailed
0.05	19	3.182	two-tailed
0.05	20	3.182	two-tailed
0.05	21	3.182	two-tailed
0.05	22	3.182	two-tailed
0.05	23	3.182	two-tailed
0.05	24	3.182	two-tailed
0.05	25	3.182	two-tailed
0.05	26	3.182	two-tailed
0.05	27	3.182	two-tailed
0.05	28	3.182	two-tailed
0.05	29	3.182	two-tailed
0.05	30	3.182	two-tailed
0.05	31	3.182	two-tailed
0.05	32	3.182	two-tailed
0.05	33	3.182	two-tailed
0.05	34	3.182	two-tailed
0.05	35	3.182	two-tailed
0.05	36	3.182	two-tailed
0.05	37	3.182	two-tailed
0.05	38	3.182	two-tailed
0.05	39	3.182	two-tailed
0.05	40	3.182	two-tailed
0.05	41	3.182	two-tailed
0.05	42	3.182	two-tailed
0.05	43	3.182	two-tailed
0.05	44	3.182	two-tailed
0.05	45	3.182	two-tailed
0.05	46	3.182	two-tailed
0.05	47	3.182	two-tailed
0.05	48	3.182	two-tailed
0.05	49	3.182	two-tailed
0.05	50	3.182	two-tailed
0.05	51	3.182	two-tailed
0.05	52	3.182	two-tailed
0.05	53	3.182	two-tailed
0.05	54	3.182	two-tailed
0.05	55	3.182	two-tailed
0.05	56	3.182	two-tailed
0.05	57	3.182	two-tailed
0.05	58	3.182	two-tailed
0.05	59	3.182	two-tailed
0.05	60	3.182	two-tailed
0.05	61	3.182	two-tailed
0.05	62	3.182	two-tailed
0.05	63	3.182	two-tailed
0.05	64	3.182	two-tailed
0.05	65	3.182	two-tailed
0.05	66	3.182	two-tailed
0.05	67	3.182	two-tailed
0.05	68	3.182	two-tailed
0.05	69	3.182	two-tailed
0.05	70	3.182	two-tailed
0.05	71	3.182	two-tailed
0.05	72	3.182	two-tailed
0.05	73	3.182	two-tailed
0.05	74	3.182	two-tailed
0.05	75	3.182	two-tailed
0.05	76	3.182	two-tailed
0.05	77	3.182	two-tailed
0.05	78	3.182	two-tailed
0.05	79	3.182	two-tailed
0.05	80	3.182	two-tailed
0.05	81	3.182	two-tailed
0.05	82	3.182	two-tailed
0.05	83	3.182	two-tailed
0.05	84	3.182	two-tailed
0.05	85	3.182	two-tailed
0.05	86	3.182	two-tailed
0.05	87	3.182	two-tailed
0.05	88	3.182	two-tailed
0.05	89	3.182	two-tailed
0.05	90	3.182	two-tailed
0.05	91	3.182	two-tailed
0.05	92	3.182	two-tailed
0.05	93	3.182	two-tailed
0.05	94	3.182	two-tailed
0.05	95	3.182	two-tailed
0.05	96	3.182	two-tailed
0.05	97	3.182	two-tailed
0.05	98	3.182	two-tailed
0.01	3	3.182	two-tailed
0.01	4	3.182	two-tailed
0.01	5	3.182	two-tailed
0.01	6	3.182	two-tailed
0.01	7	3.182	two-tailed
0.01	8	3.182	two-tailed
0.01	9	3.182	two-tailed
0.01	10	3.182	two-tailed
0.01	11	3.182	two-tailed
0.01	12	3.182	two-tailed
0.01	13	3.182	two-tailed
0.01	14	3.182	two-tailed
0.01	15	3.182	two-tailed
0.01	16	3.182	two-tailed
0.01	17	3.182	two-tailed
0.01	18	3.182	two-tailed
0.01	19	3.182	two-tailed
0.01	20	3.182	two-tailed
0.01	21	3.182	two-tailed
0.01	22	3.182	two-tailed
0.01	23	3.182	two-tailed
0.01	24	3.182	two-tailed
0.01	25	3.182	two-tailed
0.01	26	3.182	two-tailed
0.01	27	3.182	two-tailed
0.01	28	3.182	two-tailed
0.01	29	3.182	two-tailed
0.01	30	3.182	two-tailed
0.01	31	3.182	two-tailed
0.01	32	3.182	two-tailed
0.01	33	3.182	two-tailed
0.01	34	3.182	two-tailed
0.01	35	3.182	two-tailed
0.01	36	3.182	two-tailed
0.01	37	3.182	two-tailed
0.01	38	3.182	two-tailed
0.01	39	3.182	two-tailed
0.01	40	3.182	two-tailed
0.01	41	3.182	two-tailed
0.01	42	3.182	two-tailed
0.01	43	3.182	two-tailed
0.01	44	3.182	two-tailed
0.01	45	3.182	two-tailed
0.01	46	3.182	two-tailed
0.01	47	3.182	two-tailed
0.01	48	3.182	two-tailed
0.01	49	3.182	two-tailed
0.01	50	3.182	two-tailed
0.01	51	3.182	two-tailed
0.01	52	3.182	two-tailed
0.01	53	3.182	two-tailed
0.01	54	3.182	two-tailed
0.01	55	3.182	two-tailed
0.01	56	3.182	two-tailed
0.01	57	3.182	two-tailed
0.01	58	3.182	two-tailed
0.01	59	3.182	two-tailed
0.01	60	3.182	two-tailed
0.01	61	3.182	two-tailed
0.01	62	3.182	two-tailed
0.01	63	3.182	two-tailed
0.01	64	3.182	two-tailed
0.01	65	3.182	two-tailed
0.01	66	3.182	two-tailed
0.01	67	3.182	two-tailed
0.01	68	3.182	two-tailed
0.01	69	3.182	two-tailed
0.01	70	3.182	two-tailed
0.01	71	3.182	two-tailed
0.01	72	3.182	two-tailed
0.01	73	3.182	two-tailed
0.01	74	3.182	two-tailed
0.01	75	3.182	two-tailed
0.01	76	3.182	two-tailed
0.01	77	3.182	two-tailed
0.01	78	3.182	two-tailed
0.01	79	3.182	two-tailed
0.01	80	3.182	two-tailed
0.01	81	3.182	two-tailed
0.01	82	3.182	two-tailed
0.01	83	3.182	two-tailed
0.01	84	3.182	two-tailed
0.01	85	3.182	two-tailed
0.01	86	3.182	two-tailed
0.01	87	3.182	two-tailed
0.01	88	3.182	two-tailed
0.01	89	3.182	two-tailed
0.01	90	3.182	two-tailed
0.01	91	3.182	two-tailed
0.01	92	3.182	two-tailed
0.01	93	3.182	two-tailed
0.01	94	3.182	two-tailed
0.01	95	3.182	two-tailed
0.01	96	3.182	two-tailed
0.01	97	3.182	two-tailed
0.01	98	3.182	two-tailed

To interpret the F-table containing critical F-values for various degrees of freedom and significance levels, follow these steps:

Identify the degrees of freedom: Determine the numerator degrees of freedom (df1) and the denominator degrees of freedom (df2) for your data. This typically depends on the specific statistical test or model you are using, such as ANOVA or regression analysis.
Choose the significance level (α): Select the desired significance level (α) for your test. Commonly used significance levels are 0.05 and 0.01. The significance level represents the probability of rejecting the null hypothesis when it is true.
Locate the critical F-value: In the F-table, find the row with the correct df1 and the column with the correct df2. At the intersection of this row and column, locate the critical F-value for your chosen significance level (α).
Calculate the F-value: Using your data, calculate the F-value (F) as part of your statistical test or model.
Compare the F-value with the critical F-value: If the calculated F-value is greater than the critical F-value from the table, you can reject the null hypothesis, suggesting that there is a significant effect or relationship between the variables under consideration. If the calculated F-value is less than or equal to the critical F-value, you fail to reject the null hypothesis, meaning that there is not enough evidence to suggest a significant effect or relationship between the variables.

Keep in mind that rejecting or failing to reject the null hypothesis does not prove causation, but rather indicates the presence or absence of a significant effect or relationship between the variables under certain assumptions. Also, remember that the F-table provides critical F-values for specific degrees of freedom and significance levels, so ensure that you use the correct values when interpreting the table.

For the F-test:

df1 (numerator degrees of freedom): This typically represents the degrees of freedom associated with the factor or group being tested. In ANOVA, for example, df1 is the number of groups minus one (k - 1), where k is the number of groups being compared.
df2 (denominator degrees of freedom): This typically represents the degrees of freedom associated with the error or residual variation within the groups. In ANOVA, for example, df2 is the total number of observations minus the number of groups (N - k), where N is the total number of observations across all groups.

Critical F-values for F-test
df1	df2	alpha	critical_f_value
1	1	0.05	161.448
2	1	0.05	199.500
3	1	0.05	215.707
4	1	0.05	224.583
5	1	0.05	230.162
6	1	0.05	233.986
7	1	0.05	236.768
8	1	0.05	238.883
9	1	0.05	240.543
10	1	0.05	241.882
1	2	0.05	18.513
2	2	0.05	19.000
3	2	0.05	19.164
4	2	0.05	19.247
5	2	0.05	19.296
6	2	0.05	19.330
7	2	0.05	19.353
8	2	0.05	19.371
9	2	0.05	19.385
10	2	0.05	19.396
1	3	0.05	10.128
2	3	0.05	9.552
3	3	0.05	9.277
4	3	0.05	9.117
5	3	0.05	9.013
6	3	0.05	8.941
7	3	0.05	8.887
8	3	0.05	8.845
9	3	0.05	8.812
10	3	0.05	8.786
1	4	0.05	7.709
2	4	0.05	6.944
3	4	0.05	6.591
4	4	0.05	6.388
5	4	0.05	6.256
6	4	0.05	6.163
7	4	0.05	6.094
8	4	0.05	6.041
9	4	0.05	5.999
10	4	0.05	5.964
1	5	0.05	6.608
2	5	0.05	5.786
3	5	0.05	5.409
4	5	0.05	5.192
5	5	0.05	5.050
6	5	0.05	4.950
7	5	0.05	4.876
8	5	0.05	4.818
9	5	0.05	4.772
10	5	0.05	4.735
1	6	0.05	5.987
2	6	0.05	5.143
3	6	0.05	4.757
4	6	0.05	4.534
5	6	0.05	4.387
6	6	0.05	4.284
7	6	0.05	4.207
8	6	0.05	4.147
9	6	0.05	4.099
10	6	0.05	4.060
1	7	0.05	5.591
2	7	0.05	4.737
3	7	0.05	4.347
4	7	0.05	4.120
5	7	0.05	3.972
6	7	0.05	3.866
7	7	0.05	3.787
8	7	0.05	3.726
9	7	0.05	3.677
10	7	0.05	3.637
1	8	0.05	5.318
2	8	0.05	4.459
3	8	0.05	4.066
4	8	0.05	3.838
5	8	0.05	3.687
6	8	0.05	3.581
7	8	0.05	3.500
8	8	0.05	3.438
9	8	0.05	3.388
10	8	0.05	3.347
1	9	0.05	5.117
2	9	0.05	4.256
3	9	0.05	3.863
4	9	0.05	3.633
5	9	0.05	3.482
6	9	0.05	3.374
7	9	0.05	3.293
8	9	0.05	3.230
9	9	0.05	3.179
10	9	0.05	3.137
1	10	0.05	4.965
2	10	0.05	4.103
3	10	0.05	3.708
4	10	0.05	3.478
5	10	0.05	3.326
6	10	0.05	3.217
7	10	0.05	3.135
8	10	0.05	3.072
9	10	0.05	3.020
10	10	0.05	2.978
1	11	0.05	4.844
2	11	0.05	3.982
3	11	0.05	3.587
4	11	0.05	3.357
5	11	0.05	3.204
6	11	0.05	3.095
7	11	0.05	3.012
8	11	0.05	2.948
9	11	0.05	2.896
10	11	0.05	2.854
1	12	0.05	4.747
2	12	0.05	3.885
3	12	0.05	3.490
4	12	0.05	3.259
5	12	0.05	3.106
6	12	0.05	2.996
7	12	0.05	2.913
8	12	0.05	2.849
9	12	0.05	2.796
10	12	0.05	2.753
1	13	0.05	4.667
2	13	0.05	3.806
3	13	0.05	3.411
4	13	0.05	3.179
5	13	0.05	3.025
6	13	0.05	2.915
7	13	0.05	2.832
8	13	0.05	2.767
9	13	0.05	2.714
10	13	0.05	2.671
1	14	0.05	4.600
2	14	0.05	3.739
3	14	0.05	3.344
4	14	0.05	3.112
5	14	0.05	2.958
6	14	0.05	2.848
7	14	0.05	2.764
8	14	0.05	2.699
9	14	0.05	2.646
10	14	0.05	2.602
1	15	0.05	4.543
2	15	0.05	3.682
3	15	0.05	3.287
4	15	0.05	3.056
5	15	0.05	2.901
6	15	0.05	2.790
7	15	0.05	2.707
8	15	0.05	2.641
9	15	0.05	2.588
10	15	0.05	2.544
1	16	0.05	4.494
2	16	0.05	3.634
3	16	0.05	3.239
4	16	0.05	3.007
5	16	0.05	2.852
6	16	0.05	2.741
7	16	0.05	2.657
8	16	0.05	2.591
9	16	0.05	2.538
10	16	0.05	2.494
1	17	0.05	4.451
2	17	0.05	3.592
3	17	0.05	3.197
4	17	0.05	2.965
5	17	0.05	2.810
6	17	0.05	2.699
7	17	0.05	2.614
8	17	0.05	2.548
9	17	0.05	2.494
10	17	0.05	2.450
1	18	0.05	4.414
2	18	0.05	3.555
3	18	0.05	3.160
4	18	0.05	2.928
5	18	0.05	2.773
6	18	0.05	2.661
7	18	0.05	2.577
8	18	0.05	2.510
9	18	0.05	2.456
10	18	0.05	2.412
1	19	0.05	4.381
2	19	0.05	3.522
3	19	0.05	3.127
4	19	0.05	2.895
5	19	0.05	2.740
6	19	0.05	2.628
7	19	0.05	2.544
8	19	0.05	2.477
9	19	0.05	2.423
10	19	0.05	2.378
1	20	0.05	4.351
2	20	0.05	3.493
3	20	0.05	3.098
4	20	0.05	2.866
5	20	0.05	2.711
6	20	0.05	2.599
7	20	0.05	2.514
8	20	0.05	2.447
9	20	0.05	2.393
10	20	0.05	2.348
1	21	0.05	4.325
2	21	0.05	3.467
3	21	0.05	3.072
4	21	0.05	2.840
5	21	0.05	2.685
6	21	0.05	2.573
7	21	0.05	2.488
8	21	0.05	2.420
9	21	0.05	2.366
10	21	0.05	2.321
1	22	0.05	4.301
2	22	0.05	3.443
3	22	0.05	3.049
4	22	0.05	2.817
5	22	0.05	2.661
6	22	0.05	2.549
7	22	0.05	2.464
8	22	0.05	2.397
9	22	0.05	2.342
10	22	0.05	2.297
1	23	0.05	4.279
2	23	0.05	3.422
3	23	0.05	3.028
4	23	0.05	2.796
5	23	0.05	2.640
6	23	0.05	2.528
7	23	0.05	2.442
8	23	0.05	2.375
9	23	0.05	2.320
10	23	0.05	2.275
1	24	0.05	4.260
2	24	0.05	3.403
3	24	0.05	3.009
4	24	0.05	2.776
5	24	0.05	2.621
6	24	0.05	2.508
7	24	0.05	2.423
8	24	0.05	2.355
9	24	0.05	2.300
10	24	0.05	2.255
1	25	0.05	4.242
2	25	0.05	3.385
3	25	0.05	2.991
4	25	0.05	2.759
5	25	0.05	2.603
6	25	0.05	2.490
7	25	0.05	2.405
8	25	0.05	2.337
9	25	0.05	2.282
10	25	0.05	2.236
1	26	0.05	4.225
2	26	0.05	3.369
3	26	0.05	2.975
4	26	0.05	2.743
5	26	0.05	2.587
6	26	0.05	2.474
7	26	0.05	2.388
8	26	0.05	2.321
9	26	0.05	2.265
10	26	0.05	2.220
1	27	0.05	4.210
2	27	0.05	3.354
3	27	0.05	2.960
4	27	0.05	2.728
5	27	0.05	2.572
6	27	0.05	2.459
7	27	0.05	2.373
8	27	0.05	2.305
9	27	0.05	2.250
10	27	0.05	2.204
1	28	0.05	4.196
2	28	0.05	3.340
3	28	0.05	2.947
4	28	0.05	2.714
5	28	0.05	2.558
6	28	0.05	2.445
7	28	0.05	2.359
8	28	0.05	2.291
9	28	0.05	2.236
10	28	0.05	2.190
1	29	0.05	4.183
2	29	0.05	3.328
3	29	0.05	2.934
4	29	0.05	2.701
5	29	0.05	2.545
6	29	0.05	2.432
7	29	0.05	2.346
8	29	0.05	2.278
9	29	0.05	2.223
10	29	0.05	2.177
1	30	0.05	4.171
2	30	0.05	3.316
3	30	0.05	2.922
4	30	0.05	2.690
5	30	0.05	2.534
6	30	0.05	2.421
7	30	0.05	2.334
8	30	0.05	2.266
9	30	0.05	2.211
10	30	0.05	2.165
1	31	0.05	4.160
2	31	0.05	3.305
3	31	0.05	2.911
4	31	0.05	2.679
5	31	0.05	2.523
6	31	0.05	2.409
7	31	0.05	2.323
8	31	0.05	2.255
9	31	0.05	2.199
10	31	0.05	2.153
1	32	0.05	4.149
2	32	0.05	3.295
3	32	0.05	2.901
4	32	0.05	2.668
5	32	0.05	2.512
6	32	0.05	2.399
7	32	0.05	2.313
8	32	0.05	2.244
9	32	0.05	2.189
10	32	0.05	2.142
1	33	0.05	4.139
2	33	0.05	3.285
3	33	0.05	2.892
4	33	0.05	2.659
5	33	0.05	2.503
6	33	0.05	2.389
7	33	0.05	2.303
8	33	0.05	2.235
9	33	0.05	2.179
10	33	0.05	2.133
1	34	0.05	4.130
2	34	0.05	3.276
3	34	0.05	2.883
4	34	0.05	2.650
5	34	0.05	2.494
6	34	0.05	2.380
7	34	0.05	2.294
8	34	0.05	2.225
9	34	0.05	2.170
10	34	0.05	2.123
1	35	0.05	4.121
2	35	0.05	3.267
3	35	0.05	2.874
4	35	0.05	2.641
5	35	0.05	2.485
6	35	0.05	2.372
7	35	0.05	2.285
8	35	0.05	2.217
9	35	0.05	2.161
10	35	0.05	2.114
1	36	0.05	4.113
2	36	0.05	3.259
3	36	0.05	2.866
4	36	0.05	2.634
5	36	0.05	2.477
6	36	0.05	2.364
7	36	0.05	2.277
8	36	0.05	2.209
9	36	0.05	2.153
10	36	0.05	2.106
1	37	0.05	4.105
2	37	0.05	3.252
3	37	0.05	2.859
4	37	0.05	2.626
5	37	0.05	2.470
6	37	0.05	2.356
7	37	0.05	2.270
8	37	0.05	2.201
9	37	0.05	2.145
10	37	0.05	2.098
1	38	0.05	4.098
2	38	0.05	3.245
3	38	0.05	2.852
4	38	0.05	2.619
5	38	0.05	2.463
6	38	0.05	2.349
7	38	0.05	2.262
8	38	0.05	2.194
9	38	0.05	2.138
10	38	0.05	2.091
1	39	0.05	4.091
2	39	0.05	3.238
3	39	0.05	2.845
4	39	0.05	2.612
5	39	0.05	2.456
6	39	0.05	2.342
7	39	0.05	2.255
8	39	0.05	2.187
9	39	0.05	2.131
10	39	0.05	2.084
1	40	0.05	4.085
2	40	0.05	3.232
3	40	0.05	2.839
4	40	0.05	2.606
5	40	0.05	2.449
6	40	0.05	2.336
7	40	0.05	2.249
8	40	0.05	2.180
9	40	0.05	2.124
10	40	0.05	2.077
1	41	0.05	4.079
2	41	0.05	3.226
3	41	0.05	2.833
4	41	0.05	2.600
5	41	0.05	2.443
6	41	0.05	2.330
7	41	0.05	2.243
8	41	0.05	2.174
9	41	0.05	2.118
10	41	0.05	2.071
1	42	0.05	4.073
2	42	0.05	3.220
3	42	0.05	2.827
4	42	0.05	2.594
5	42	0.05	2.438
6	42	0.05	2.324
7	42	0.05	2.237
8	42	0.05	2.168
9	42	0.05	2.112
10	42	0.05	2.065
1	43	0.05	4.067
2	43	0.05	3.214
3	43	0.05	2.822
4	43	0.05	2.589
5	43	0.05	2.432
6	43	0.05	2.318
7	43	0.05	2.232
8	43	0.05	2.163
9	43	0.05	2.106
10	43	0.05	2.059
1	44	0.05	4.062
2	44	0.05	3.209
3	44	0.05	2.816
4	44	0.05	2.584
5	44	0.05	2.427
6	44	0.05	2.313
7	44	0.05	2.226
8	44	0.05	2.157
9	44	0.05	2.101
10	44	0.05	2.054
1	45	0.05	4.057
2	45	0.05	3.204
3	45	0.05	2.812
4	45	0.05	2.579
5	45	0.05	2.422
6	45	0.05	2.308
7	45	0.05	2.221
8	45	0.05	2.152
9	45	0.05	2.096
10	45	0.05	2.049
1	46	0.05	4.052
2	46	0.05	3.200
3	46	0.05	2.807
4	46	0.05	2.574
5	46	0.05	2.417
6	46	0.05	2.304
7	46	0.05	2.216
8	46	0.05	2.147
9	46	0.05	2.091
10	46	0.05	2.044
1	47	0.05	4.047
2	47	0.05	3.195
3	47	0.05	2.802
4	47	0.05	2.570
5	47	0.05	2.413
6	47	0.05	2.299
7	47	0.05	2.212
8	47	0.05	2.143
9	47	0.05	2.086
10	47	0.05	2.039
1	48	0.05	4.043
2	48	0.05	3.191
3	48	0.05	2.798
4	48	0.05	2.565
5	48	0.05	2.409
6	48	0.05	2.295
7	48	0.05	2.207
8	48	0.05	2.138
9	48	0.05	2.082
10	48	0.05	2.035
1	49	0.05	4.038
2	49	0.05	3.187
3	49	0.05	2.794
4	49	0.05	2.561
5	49	0.05	2.404
6	49	0.05	2.290
7	49	0.05	2.203
8	49	0.05	2.134
9	49	0.05	2.077
10	49	0.05	2.030
1	50	0.05	4.034
2	50	0.05	3.183
3	50	0.05	2.790
4	50	0.05	2.557
5	50	0.05	2.400
6	50	0.05	2.286
7	50	0.05	2.199
8	50	0.05	2.130
9	50	0.05	2.073
10	50	0.05	2.026
1	1	0.01	4052.181
2	1	0.01	4999.500
3	1	0.01	5403.352
4	1	0.01	5624.583
5	1	0.01	5763.650
6	1	0.01	5858.986
7	1	0.01	5928.356
8	1	0.01	5981.070
9	1	0.01	6022.473
10	1	0.01	6055.847
1	2	0.01	98.503
2	2	0.01	99.000
3	2	0.01	99.166
4	2	0.01	99.249
5	2	0.01	99.299
6	2	0.01	99.333
7	2	0.01	99.356
8	2	0.01	99.374
9	2	0.01	99.388
10	2	0.01	99.399
1	3	0.01	34.116
2	3	0.01	30.817
3	3	0.01	29.457
4	3	0.01	28.710
5	3	0.01	28.237
6	3	0.01	27.911
7	3	0.01	27.672
8	3	0.01	27.489
9	3	0.01	27.345
10	3	0.01	27.229
1	4	0.01	21.198
2	4	0.01	18.000
3	4	0.01	16.694
4	4	0.01	15.977
5	4	0.01	15.522
6	4	0.01	15.207
7	4	0.01	14.976
8	4	0.01	14.799
9	4	0.01	14.659
10	4	0.01	14.546
1	5	0.01	16.258
2	5	0.01	13.274
3	5	0.01	12.060
4	5	0.01	11.392
5	5	0.01	10.967
6	5	0.01	10.672
7	5	0.01	10.456
8	5	0.01	10.289
9	5	0.01	10.158
10	5	0.01	10.051
1	6	0.01	13.745
2	6	0.01	10.925
3	6	0.01	9.780
4	6	0.01	9.148
5	6	0.01	8.746
6	6	0.01	8.466
7	6	0.01	8.260
8	6	0.01	8.102
9	6	0.01	7.976
10	6	0.01	7.874
1	7	0.01	12.246
2	7	0.01	9.547
3	7	0.01	8.451
4	7	0.01	7.847
5	7	0.01	7.460
6	7	0.01	7.191
7	7	0.01	6.993
8	7	0.01	6.840
9	7	0.01	6.719
10	7	0.01	6.620
1	8	0.01	11.259
2	8	0.01	8.649
3	8	0.01	7.591
4	8	0.01	7.006
5	8	0.01	6.632
6	8	0.01	6.371
7	8	0.01	6.178
8	8	0.01	6.029
9	8	0.01	5.911
10	8	0.01	5.814
1	9	0.01	10.561
2	9	0.01	8.022
3	9	0.01	6.992
4	9	0.01	6.422
5	9	0.01	6.057
6	9	0.01	5.802
7	9	0.01	5.613
8	9	0.01	5.467
9	9	0.01	5.351
10	9	0.01	5.257
1	10	0.01	10.044
2	10	0.01	7.559
3	10	0.01	6.552
4	10	0.01	5.994
5	10	0.01	5.636
6	10	0.01	5.386
7	10	0.01	5.200
8	10	0.01	5.057
9	10	0.01	4.942
10	10	0.01	4.849
1	11	0.01	9.646
2	11	0.01	7.206
3	11	0.01	6.217
4	11	0.01	5.668
5	11	0.01	5.316
6	11	0.01	5.069
7	11	0.01	4.886
8	11	0.01	4.744
9	11	0.01	4.632
10	11	0.01	4.539
1	12	0.01	9.330
2	12	0.01	6.927
3	12	0.01	5.953
4	12	0.01	5.412
5	12	0.01	5.064
6	12	0.01	4.821
7	12	0.01	4.640
8	12	0.01	4.499
9	12	0.01	4.388
10	12	0.01	4.296
1	13	0.01	9.074
2	13	0.01	6.701
3	13	0.01	5.739
4	13	0.01	5.205
5	13	0.01	4.862
6	13	0.01	4.620
7	13	0.01	4.441
8	13	0.01	4.302
9	13	0.01	4.191
10	13	0.01	4.100
1	14	0.01	8.862
2	14	0.01	6.515
3	14	0.01	5.564
4	14	0.01	5.035
5	14	0.01	4.695
6	14	0.01	4.456
7	14	0.01	4.278
8	14	0.01	4.140
9	14	0.01	4.030
10	14	0.01	3.939
1	15	0.01	8.683
2	15	0.01	6.359
3	15	0.01	5.417
4	15	0.01	4.893
5	15	0.01	4.556
6	15	0.01	4.318
7	15	0.01	4.142
8	15	0.01	4.004
9	15	0.01	3.895
10	15	0.01	3.805
1	16	0.01	8.531
2	16	0.01	6.226
3	16	0.01	5.292
4	16	0.01	4.773
5	16	0.01	4.437
6	16	0.01	4.202
7	16	0.01	4.026
8	16	0.01	3.890
9	16	0.01	3.780
10	16	0.01	3.691
1	17	0.01	8.400
2	17	0.01	6.112
3	17	0.01	5.185
4	17	0.01	4.669
5	17	0.01	4.336
6	17	0.01	4.102
7	17	0.01	3.927
8	17	0.01	3.791
9	17	0.01	3.682
10	17	0.01	3.593
1	18	0.01	8.285
2	18	0.01	6.013
3	18	0.01	5.092
4	18	0.01	4.579
5	18	0.01	4.248
6	18	0.01	4.015
7	18	0.01	3.841
8	18	0.01	3.705
9	18	0.01	3.597
10	18	0.01	3.508
1	19	0.01	8.185
2	19	0.01	5.926
3	19	0.01	5.010
4	19	0.01	4.500
5	19	0.01	4.171
6	19	0.01	3.939
7	19	0.01	3.765
8	19	0.01	3.631
9	19	0.01	3.523
10	19	0.01	3.434
1	20	0.01	8.096
2	20	0.01	5.849
3	20	0.01	4.938
4	20	0.01	4.431
5	20	0.01	4.103
6	20	0.01	3.871
7	20	0.01	3.699
8	20	0.01	3.564
9	20	0.01	3.457
10	20	0.01	3.368
1	21	0.01	8.017
2	21	0.01	5.780
3	21	0.01	4.874
4	21	0.01	4.369
5	21	0.01	4.042
6	21	0.01	3.812
7	21	0.01	3.640
8	21	0.01	3.506
9	21	0.01	3.398
10	21	0.01	3.310
1	22	0.01	7.945
2	22	0.01	5.719
3	22	0.01	4.817
4	22	0.01	4.313
5	22	0.01	3.988
6	22	0.01	3.758
7	22	0.01	3.587
8	22	0.01	3.453
9	22	0.01	3.346
10	22	0.01	3.258
1	23	0.01	7.881
2	23	0.01	5.664
3	23	0.01	4.765
4	23	0.01	4.264
5	23	0.01	3.939
6	23	0.01	3.710
7	23	0.01	3.539
8	23	0.01	3.406
9	23	0.01	3.299
10	23	0.01	3.211
1	24	0.01	7.823
2	24	0.01	5.614
3	24	0.01	4.718
4	24	0.01	4.218
5	24	0.01	3.895
6	24	0.01	3.667
7	24	0.01	3.496
8	24	0.01	3.363
9	24	0.01	3.256
10	24	0.01	3.168
1	25	0.01	7.770
2	25	0.01	5.568
3	25	0.01	4.675
4	25	0.01	4.177
5	25	0.01	3.855
6	25	0.01	3.627
7	25	0.01	3.457
8	25	0.01	3.324
9	25	0.01	3.217
10	25	0.01	3.129
1	26	0.01	7.721
2	26	0.01	5.526
3	26	0.01	4.637
4	26	0.01	4.140
5	26	0.01	3.818
6	26	0.01	3.591
7	26	0.01	3.421
8	26	0.01	3.288
9	26	0.01	3.182
10	26	0.01	3.094
1	27	0.01	7.677
2	27	0.01	5.488
3	27	0.01	4.601
4	27	0.01	4.106
5	27	0.01	3.785
6	27	0.01	3.558
7	27	0.01	3.388
8	27	0.01	3.256
9	27	0.01	3.149
10	27	0.01	3.062
1	28	0.01	7.636
2	28	0.01	5.453
3	28	0.01	4.568
4	28	0.01	4.074
5	28	0.01	3.754
6	28	0.01	3.528
7	28	0.01	3.358
8	28	0.01	3.226
9	28	0.01	3.120
10	28	0.01	3.032
1	29	0.01	7.598
2	29	0.01	5.420
3	29	0.01	4.538
4	29	0.01	4.045
5	29	0.01	3.725
6	29	0.01	3.499
7	29	0.01	3.330
8	29	0.01	3.198
9	29	0.01	3.092
10	29	0.01	3.005
1	30	0.01	7.562
2	30	0.01	5.390
3	30	0.01	4.510
4	30	0.01	4.018
5	30	0.01	3.699
6	30	0.01	3.473
7	30	0.01	3.304
8	30	0.01	3.173
9	30	0.01	3.067
10	30	0.01	2.979
1	31	0.01	7.530
2	31	0.01	5.362
3	31	0.01	4.484
4	31	0.01	3.993
5	31	0.01	3.675
6	31	0.01	3.449
7	31	0.01	3.281
8	31	0.01	3.149
9	31	0.01	3.043
10	31	0.01	2.955
1	32	0.01	7.499
2	32	0.01	5.336
3	32	0.01	4.459
4	32	0.01	3.969
5	32	0.01	3.652
6	32	0.01	3.427
7	32	0.01	3.258
8	32	0.01	3.127
9	32	0.01	3.021
10	32	0.01	2.934
1	33	0.01	7.471
2	33	0.01	5.312
3	33	0.01	4.437
4	33	0.01	3.948
5	33	0.01	3.630
6	33	0.01	3.406
7	33	0.01	3.238
8	33	0.01	3.106
9	33	0.01	3.000
10	33	0.01	2.913
1	34	0.01	7.444
2	34	0.01	5.289
3	34	0.01	4.416
4	34	0.01	3.927
5	34	0.01	3.611
6	34	0.01	3.386
7	34	0.01	3.218
8	34	0.01	3.087
9	34	0.01	2.981
10	34	0.01	2.894
1	35	0.01	7.419
2	35	0.01	5.268
3	35	0.01	4.396
4	35	0.01	3.908
5	35	0.01	3.592
6	35	0.01	3.368
7	35	0.01	3.200
8	35	0.01	3.069
9	35	0.01	2.963
10	35	0.01	2.876
1	36	0.01	7.396
2	36	0.01	5.248
3	36	0.01	4.377
4	36	0.01	3.890
5	36	0.01	3.574
6	36	0.01	3.351
7	36	0.01	3.183
8	36	0.01	3.052
9	36	0.01	2.946
10	36	0.01	2.859
1	37	0.01	7.373
2	37	0.01	5.229
3	37	0.01	4.360
4	37	0.01	3.873
5	37	0.01	3.558
6	37	0.01	3.334
7	37	0.01	3.167
8	37	0.01	3.036
9	37	0.01	2.930
10	37	0.01	2.843
1	38	0.01	7.353
2	38	0.01	5.211
3	38	0.01	4.343
4	38	0.01	3.858
5	38	0.01	3.542
6	38	0.01	3.319
7	38	0.01	3.152
8	38	0.01	3.021
9	38	0.01	2.915
10	38	0.01	2.828
1	39	0.01	7.333
2	39	0.01	5.194
3	39	0.01	4.327
4	39	0.01	3.843
5	39	0.01	3.528
6	39	0.01	3.305
7	39	0.01	3.137
8	39	0.01	3.006
9	39	0.01	2.901
10	39	0.01	2.814
1	40	0.01	7.314
2	40	0.01	5.179
3	40	0.01	4.313
4	40	0.01	3.828
5	40	0.01	3.514
6	40	0.01	3.291
7	40	0.01	3.124
8	40	0.01	2.993
9	40	0.01	2.888
10	40	0.01	2.801
1	41	0.01	7.296
2	41	0.01	5.163
3	41	0.01	4.299
4	41	0.01	3.815
5	41	0.01	3.501
6	41	0.01	3.278
7	41	0.01	3.111
8	41	0.01	2.980
9	41	0.01	2.875
10	41	0.01	2.788
1	42	0.01	7.280
2	42	0.01	5.149
3	42	0.01	4.285
4	42	0.01	3.802
5	42	0.01	3.488
6	42	0.01	3.266
7	42	0.01	3.099
8	42	0.01	2.968
9	42	0.01	2.863
10	42	0.01	2.776
1	43	0.01	7.264
2	43	0.01	5.136
3	43	0.01	4.273
4	43	0.01	3.790
5	43	0.01	3.476
6	43	0.01	3.254
7	43	0.01	3.087
8	43	0.01	2.957
9	43	0.01	2.851
10	43	0.01	2.764
1	44	0.01	7.248
2	44	0.01	5.123
3	44	0.01	4.261
4	44	0.01	3.778
5	44	0.01	3.465
6	44	0.01	3.243
7	44	0.01	3.076
8	44	0.01	2.946
9	44	0.01	2.840
10	44	0.01	2.754
1	45	0.01	7.234
2	45	0.01	5.110
3	45	0.01	4.249
4	45	0.01	3.767
5	45	0.01	3.454
6	45	0.01	3.232
7	45	0.01	3.066
8	45	0.01	2.935
9	45	0.01	2.830
10	45	0.01	2.743
1	46	0.01	7.220
2	46	0.01	5.099
3	46	0.01	4.238
4	46	0.01	3.757
5	46	0.01	3.444
6	46	0.01	3.222
7	46	0.01	3.056
8	46	0.01	2.925
9	46	0.01	2.820
10	46	0.01	2.733
1	47	0.01	7.207
2	47	0.01	5.087
3	47	0.01	4.228
4	47	0.01	3.747
5	47	0.01	3.434
6	47	0.01	3.213
7	47	0.01	3.046
8	47	0.01	2.916
9	47	0.01	2.811
10	47	0.01	2.724
1	48	0.01	7.194
2	48	0.01	5.077
3	48	0.01	4.218
4	48	0.01	3.737
5	48	0.01	3.425
6	48	0.01	3.204
7	48	0.01	3.037
8	48	0.01	2.907
9	48	0.01	2.802
10	48	0.01	2.715
1	49	0.01	7.182
2	49	0.01	5.066
3	49	0.01	4.208
4	49	0.01	3.728
5	49	0.01	3.416
6	49	0.01	3.195
7	49	0.01	3.028
8	49	0.01	2.898
9	49	0.01	2.793
10	49	0.01	2.706
1	50	0.01	7.171
2	50	0.01	5.057
3	50	0.01	4.199
4	50	0.01	3.720
5	50	0.01	3.408
6	50	0.01	3.186
7	50	0.01	3.020
8	50	0.01	2.890
9	50	0.01	2.785
10	50	0.01	2.698