例えば,$N = 14$, $T = 20$ のとき有意水準 $5\%$ で両側検定を行うとするときは,表からパーセント点は $21$ であることが分かり,$T < 21$ ゆえ帰無仮説を棄却する。
パーセント点の横の数値は,検定統計量がちょうどパーセント点の値のときの正確な有意水準である。例の場合だと $0.04944$ である。
$N$ | 両側検定 $\alpha=0.05$ | 両側検定 $\alpha=0.01$ | 片側検定 $\alpha=0.05$ | 片側検定 $\alpha=0.01$ | ||||
---|---|---|---|---|---|---|---|---|
5 | --- | --- | --- | --- | 0 | 0.03125 | --- | --- |
6 | 0 | 0.03125 | --- | --- | 2 | 0.04688 | --- | --- |
7 | 2 | 0.04688 | --- | --- | 3 | 0.03906 | 0 | 0.00781 |
8 | 3 | 0.03906 | 0 | 0.00781 | 5 | 0.03906 | 1 | 0.00781 |
9 | 5 | 0.03906 | 1 | 0.00781 | 8 | 0.04883 | 3 | 0.00977 |
10 | 8 | 0.04883 | 3 | 0.00977 | 10 | 0.04199 | 5 | 0.00977 |
11 | 10 | 0.04199 | 5 | 0.00977 | 13 | 0.04150 | 7 | 0.00928 |
12 | 13 | 0.04248 | 7 | 0.00928 | 17 | 0.04614 | 9 | 0.00806 |
13 | 17 | 0.04785 | 9 | 0.00806 | 21 | 0.04712 | 12 | 0.00854 |
14 | 21 | 0.04944 | 12 | 0.00854 | 25 | 0.04529 | 15 | 0.00830 |
15 | 25 | 0.04791 | 15 | 0.00836 | 30 | 0.04730 | 19 | 0.00903 |
16 | 29 | 0.04431 | 19 | 0.00919 | 35 | 0.04672 | 23 | 0.00912 |
17 | 34 | 0.04477 | 23 | 0.00934 | 41 | 0.04919 | 27 | 0.00871 |
18 | 40 | 0.04828 | 27 | 0.00896 | 47 | 0.04937 | 32 | 0.00912 |
19 | 46 | 0.04937 | 32 | 0.00945 | 53 | 0.04776 | 37 | 0.00904 |
20 | 52 | 0.04844 | 37 | 0.00944 | 60 | 0.04865 | 43 | 0.00962 |
21 | 58 | 0.04599 | 42 | 0.00902 | 67 | 0.04790 | 49 | 0.00974 |
22 | 65 | 0.04616 | 48 | 0.00927 | 75 | 0.04921 | 55 | 0.00948 |
23 | 73 | 0.04844 | 54 | 0.00915 | 83 | 0.04899 | 62 | 0.00978 |
24 | 81 | 0.04906 | 61 | 0.00958 | 91 | 0.04755 | 69 | 0.00972 |
25 | 89 | 0.04826 | 68 | 0.00964 | 100 | 0.04787 | 76 | 0.00937 |
26 | 98 | 0.04935 | 75 | 0.00938 | 110 | 0.04967 | 84 | 0.00949 |
27 | 107 | 0.04910 | 83 | 0.00961 | 119 | 0.04769 | 92 | 0.00933 |
28 | 116 | 0.04775 | 91 | 0.00954 | 130 | 0.04964 | 101 | 0.00956 |
29 | 126 | 0.04803 | 100 | 0.00988 | 140 | 0.04817 | 110 | 0.00952 |
30 | 137 | 0.04971 | 109 | 0.00993 | 151 | 0.04805 | 120 | 0.00983 |
31 | 147 | 0.04789 | 118 | 0.00974 | 163 | 0.04909 | 130 | 0.00989 |
32 | 159 | 0.04977 | 128 | 0.00991 | 175 | 0.04919 | 140 | 0.00972 |
33 | 170 | 0.04843 | 138 | 0.00984 | 187 | 0.04848 | 151 | 0.00987 |
34 | 182 | 0.04838 | 148 | 0.00957 | 200 | 0.04882 | 162 | 0.00981 |
35 | 195 | 0.04946 | 159 | 0.00963 | 213 | 0.04839 | 173 | 0.00956 |
36 | 208 | 0.04964 | 171 | 0.00996 | 227 | 0.04890 | 185 | 0.00959 |
37 | 221 | 0.04904 | 182 | 0.00962 | 241 | 0.04868 | 198 | 0.00986 |
38 | 235 | 0.04947 | 194 | 0.00956 | 256 | 0.04932 | 211 | 0.00994 |
39 | 249 | 0.04915 | 207 | 0.00976 | 271 | 0.04928 | 224 | 0.00986 |
40 | 264 | 0.04976 | 220 | 0.00978 | 286 | 0.04862 | 238 | 0.00999 |
41 | 279 | 0.04966 | 233 | 0.00964 | 302 | 0.04875 | 252 | 0.00997 |
42 | 294 | 0.04892 | 247 | 0.00973 | 319 | 0.04960 | 266 | 0.00980 |
43 | 310 | 0.04904 | 261 | 0.00966 | 336 | 0.04983 | 281 | 0.00984 |
44 | 327 | 0.04994 | 276 | 0.00980 | 353 | 0.04950 | 296 | 0.00974 |
45 | 343 | 0.04885 | 291 | 0.00979 | 371 | 0.04984 | 312 | 0.00982 |
46 | 361 | 0.04987 | 307 | 0.00997 | 389 | 0.04966 | 328 | 0.00977 |
47 | 378 | 0.04901 | 322 | 0.00969 | 407 | 0.04899 | 345 | 0.00989 |
48 | 396 | 0.04889 | 339 | 0.00992 | 426 | 0.04896 | 362 | 0.00988 |
49 | 415 | 0.04943 | 355 | 0.00971 | 446 | 0.04949 | 379 | 0.00976 |
50 | 434 | 0.04945 | 373 | 0.00996 | 466 | 0.04954 | 397 | 0.00979 |
51 | 453 | 0.04897 | 390 | 0.00981 | 486 | 0.04916 | 416 | 0.00997 |
52 | 473 | 0.04912 | 408 | 0.00982 | 507 | 0.04931 | 434 | 0.00979 |
53 | 494 | 0.04986 | 427 | 0.00998 | 529 | 0.04996 | 454 | 0.00999 |
54 | 514 | 0.04908 | 445 | 0.00977 | 550 | 0.04928 | 473 | 0.00985 |
55 | 536 | 0.04989 | 465 | 0.00996 | 573 | 0.04998 | 493 | 0.00984 |
56 | 557 | 0.04926 | 484 | 0.00979 | 595 | 0.04941 | 514 | 0.00996 |
57 | 579 | 0.04918 | 504 | 0.00977 | 618 | 0.04933 | 535 | 0.00998 |
58 | 602 | 0.04963 | 525 | 0.00989 | 642 | 0.04969 | 556 | 0.00991 |
59 | 625 | 0.04965 | 546 | 0.00990 | 666 | 0.04967 | 578 | 0.00996 |
60 | 648 | 0.04928 | 567 | 0.00982 | 690 | 0.04931 | 600 | 0.00992 |
61 | 672 | 0.04940 | 589 | 0.00986 | 715 | 0.04938 | 623 | 0.00999 |
62 | 697 | 0.04998 | 611 | 0.00982 | 741 | 0.04984 | 646 | 0.00997 |
63 | 721 | 0.04936 | 634 | 0.00989 | 767 | 0.04995 | 669 | 0.00988 |
64 | 747 | 0.05000 | 657 | 0.00987 | 793 | 0.04974 | 693 | 0.00989 |
65 | 772 | 0.04948 | 681 | 0.00996 | 820 | 0.04991 | 718 | 0.01000 |
66 | 798 | 0.04941 | 705 | 0.00997 | 847 | 0.04978 | 742 | 0.00985 |
67 | 825 | 0.04975 | 729 | 0.00990 | 875 | 0.05000 | 768 | 0.00998 |
68 | 852 | 0.04975 | 754 | 0.00993 | 903 | 0.04992 | 793 | 0.00986 |
69 | 879 | 0.04944 | 779 | 0.00989 | 931 | 0.04956 | 819 | 0.00984 |
70 | 907 | 0.04952 | 805 | 0.00994 | 960 | 0.04954 | 846 | 0.00991 |
71 | 936 | 0.04997 | 831 | 0.00992 | 990 | 0.04985 | 873 | 0.00991 |
72 | 964 | 0.04943 | 858 | 0.01000 | 1020 | 0.04988 | 901 | 0.00999 |
73 | 994 | 0.04993 | 884 | 0.00984 | 1050 | 0.04965 | 928 | 0.00986 |
74 | 1023 | 0.04948 | 912 | 0.00993 | 1081 | 0.04972 | 957 | 0.00996 |
75 | 1053 | 0.04940 | 940 | 0.00995 | 1112 | 0.04955 | 986 | 0.00999 |
76 | 1084 | 0.04965 | 968 | 0.00991 | 1144 | 0.04967 | 1015 | 0.00995 |
77 | 1115 | 0.04962 | 997 | 0.00995 | 1176 | 0.04955 | 1044 | 0.00986 |
78 | 1147 | 0.04992 | 1026 | 0.00993 | 1209 | 0.04971 | 1075 | 0.00998 |
79 | 1179 | 0.04995 | 1056 | 0.00998 | 1242 | 0.04963 | 1105 | 0.00991 |
80 | 1211 | 0.04971 | 1086 | 0.00998 | 1276 | 0.04982 | 1136 | 0.00991 |
81 | 1244 | 0.04979 | 1116 | 0.00991 | 1310 | 0.04978 | 1168 | 0.00998 |
82 | 1277 | 0.04962 | 1147 | 0.00992 | 1345 | 0.05000 | 1200 | 0.01000 |
83 | 1311 | 0.04975 | 1178 | 0.00988 | 1380 | 0.04999 | 1232 | 0.00996 |
84 | 1345 | 0.04964 | 1210 | 0.00991 | 1415 | 0.04978 | 1265 | 0.00998 |
85 | 1380 | 0.04981 | 1242 | 0.00988 | 1451 | 0.04981 | 1298 | 0.00996 |
86 | 1415 | 0.04975 | 1275 | 0.00992 | 1487 | 0.04964 | 1332 | 0.01000 |
87 | 1451 | 0.04996 | 1308 | 0.00991 | 1524 | 0.04971 | 1366 | 0.00998 |
88 | 1487 | 0.04994 | 1342 | 0.00996 | 1561 | 0.04958 | 1400 | 0.00992 |
89 | 1523 | 0.04970 | 1376 | 0.00996 | 1599 | 0.04968 | 1435 | 0.00992 |
90 | 1560 | 0.04972 | 1410 | 0.00991 | 1638 | 0.05000 | 1471 | 0.00998 |
91 | 1597 | 0.04954 | 1445 | 0.00993 | 1676 | 0.04971 | 1507 | 0.00999 |
92 | 1635 | 0.04961 | 1480 | 0.00989 | 1715 | 0.04965 | 1543 | 0.00995 |
93 | 1674 | 0.04992 | 1516 | 0.00992 | 1755 | 0.04980 | 1580 | 0.00998 |
94 | 1712 | 0.04958 | 1552 | 0.00990 | 1795 | 0.04976 | 1617 | 0.00995 |
95 | 1752 | 0.04992 | 1589 | 0.00994 | 1836 | 0.04994 | 1655 | 0.00998 |
96 | 1791 | 0.04963 | 1626 | 0.00993 | 1877 | 0.04993 | 1693 | 0.00997 |
97 | 1832 | 0.05000 | 1664 | 0.00998 | 1918 | 0.04975 | 1731 | 0.00991 |
98 | 1872 | 0.04974 | 1702 | 0.00998 | 1960 | 0.04978 | 1770 | 0.00991 |
99 | 1913 | 0.04972 | 1740 | 0.00994 | 2003 | 0.04999 | 1810 | 0.00996 |
100 | 1955 | 0.04992 | 1779 | 0.00995 | 2045 | 0.04968 | 1850 | 0.00997 |