The Durbin-Watson tests the null hypothesis to check whether the residuals from an ordinary least-squares regression are not autocorrelated against the alternative. The Durbin-Watson statistics ranges in value from 0 to 4. A value near 2 indicates non-autocorrelation; a value toward 0 indicates positive autocorrelation; a value toward 4 indicates negative autocorrelation. Here BLUS stands for Best Linear Unbiased with Scalar covariance matrix.
| No | 1% | 2.5% | 5% | 10% |
|---|---|---|---|---|
| 5 | 0.5369 | 0.6638 | 0.8198 | 1.0506 |
| 6 | 0.5604 | 0.7207 | 0.8898 | 1.0991 |
| 7 | 0.6137 | 0.7790 | 0.9355 | 1.1403 |
| 8 | 0.6642 | 0.8242 | 0.9813 | 1.1830 |
| 9 | 0.7089 | 0.8695 | 1.0243 | 1.2184 |
| 10 | 0.7519 | 0.9110 | 1.0619 | 1.2509 |
| 11 | 0.7917 | 0.9485 | 1.0964 | 1.2799 |
| 12 | 0.8284 | 0.9829 | 1.1274 | 1.3058 |
| 13 | 0.8619 | 1.0144 | 1.1558 | 1.3294 |
| 14 | 0.8936 | 1.0432 | 1.1816 | 1.3508 |
| is | 0.9225 | 1.0698 | 1.2053 | 1.3703 |
| 16 | 0.9494 | 1.0944 | 1.2271 | 1.3882 |
| 17 | 0.9746 | 1.1171 | 1.2473 | 1.4047 |
| 18 | 0.9979 | 1.1384 | 1.2660 | 1.4199 |
| 19 | 1.0201 | 1.1581 | 1.2834 | 1.4341 |
| 20 | 1.0407 | 1.1767 | 1.2996 | 1.4473 |
| 21 | 1.0602 | 1.1940 | 1.3148 | 1.4596 |
| 22 | 1.0785 | 1.2104 | 1.3291 | 1.4711 |
| 23 | 1.0958 | 1.2258 | 1.3425 | 1.4819 |
| 24 | 1.1122 | 1.2403 | 1.3551 | 1.4921 |
| 25 | 1.1277 | 1.2540 | 1.3671 | 1.5018 |
| 26 | 1.1425 | 1.2671 | 1.3784 | 1.5109 |
| 27 | 1.1566 | 1.2795 | 1.3891 | 1.5195 |
| 28 | 1.1700 | 1.2913 | 1.3994 | 1.5277 |
| 29 | 1.1828 | 1.3025 | 1.4091 | 1.5355 |
| 30 | 1.1950 | 1.3132 | 1.4183 | 1.5429 |
| 31 | 1.2068 | 1.3235 | 1.4272 | 1.5500 |
| 32 | 1.2180 | 1.3333 | 1.4357 | 1.5567 |
| 33 | 1.2287 | 1.3427 | 1.4437 | 1.5632 |
| 34 | 1.2390 | 1.3517 | 1.4515 | 1.5694 |
| 35 | 1.2489 | 1.3603 | 1.4589 | 1.5753 |
| 36 | 1.2585 | 1.3687 | 1.4661 | 1.5810 |
| 37 | 1.2677 | 1.3767 | 1.4730 | 1.5865 |
| 38 | 1.2766 | 1.3844 | 1.4796 | 1.5917 |
| 39 | 1.2851 | 1.3918 | 1.4859 | 1.5968 |
| 40 | 1.2934 | 1.3990 | 1.4921 | 1.6017 |
| 41 | 1.3014 | 1.4059 | 1.4980 | 1.6064 |
| 42 | 1.3091 | 1.4126 | 1.5038 | 1.6110 |
| 43 | 1.3166 | 1.4191 | 1.5093 | 1.6154 |
| 44 | 1.3238 | 1.4253 | 1.5146 | 1.6196 |
| 45 | 1.3308 | 1.4314 | 1.5198 | 1.6237 |
| 46 | 1.3376 | 1.4373 | 1.5249 | 1.6277 |
| 47 | 1.3442 | 1.4430 | 1.5297 | 1.6316 |
| 48 | 1.3506 | 1.4485 | 1.5345 | 1.6353 |
| 49 | 1.3568 | 1.4539 | 1.5391 | 1.6389 |
| 50 | 1.3628 | 1.4591 | 1.5435 | 1.6425 |
| 51 | 1.3687 | 1.4641 | 1.5478 | 1.6459 |
| 52 | 1.3745 | 1.4691 | 1.5520 | 1.6492 |
| 53 | 1.3800 | 1.4738 | 1.5561 | 1.6525 |
| 54 | 1.3855 | 1.4785 | 1.5601 | 1.6556 |
| 55 | 1.3907 | 1.4831 | 1.5640 | 1.6587 |
| 56 | 1.3959 | 1.4875 | 1.5677 | 1.6617 |
| 57 | 1.4009 | 1.4918 | 1.5714 | 1.6646 |
| 58 | 1.4058 | 1.4960 | 1.5750 | 1.6674 |
| 59 | 1.4106 | 1.5002 | 1.5785 | 1.6701 |
| 60 | 1.4152 | 1.5042 | 1.5819 | 1.6728 |
