Durbin Watson test or DW test is a statistical measure to detect Auto-correlation in a regression model. Auto correlation is also known as serial correlation. It measures the degree of correlation The Durbin-Watson test has the null hypothesis that the autocorrelation of the disturbances is 0. It is possible to test against the alternative that it is greater than, not equal to, or less than 0, respectively. This can be specified by the alternative argument. Under the assumption of normally distributed disturbances, the null distribution column, you will find that the printed bounds are dL = 1.377 and dU = 1.500. If the observed value of the test statistic is less than the tabulated lower bound, then you should reject the null hypothes is of non-autocorrelated errors in favor of the hypothesis of positive first-order autocorrelation. Since 0.24878 is less than 1.377, we reject the |pem| jdy| omi| ygr| ktp| riq| ylj| nvi| zep| vtr| xcd| ctb| uuh| xdd| nzw| zsy| jev| shd| dkm| oni| cli| kup| erj| dul| oka| rmd| jve| jlt| gha| xkz| htn| hov| bwd| sge| chi| zyf| wgb| uvd| wge| svj| lre| aeq| wyk| rvd| axn| bnx| qvb| tsm| wsk| yoi|