使用 Minitab,我检查了回归假设。在这里我可以看到 x4 的残差(误差)是正态分布的。(y 是响应)。但是,它们是随机分布的吗?查看“Versus Fits”图表,它们似乎是正常分布的,但我不太确定。你怎么看?

Regression Analysis: y versus x4
The regression equation is
y = 62,1 + 4,98 x4
Predictor Coef SE Coef T P VIF
Constant 62,125 9,683 6,42 0,000
x4 4,979 2,634 1,89 0,063 1,000
S = 11,5115 R-Sq = 5,5% R-Sq(adj) = 4,0%
PRESS = 8703,56 R-Sq(pred) = 0,00%
Analysis of Variance
Source DF SS MS F P
Regression 1 473,5 473,5 3,57 0,063
Residual Error 61 8083,3 132,5
Lack of Fit 3 638,8 212,9 1,66 0,186
Pure Error 58 7444,6 128,4
Total 62 8556,9
1 rows with no replicates
Unusual Observations
Obs x4 y Fit SE Fit Residual St Resid
35 3,00 49,00 77,06 2,21 -28,06 -2,48R
56 2,00 60,00 72,08 4,54 -12,08 -1,14 X
R denotes an observation with a large standardized residual.
X denotes an observation whose X value gives it large leverage.
Durbin-Watson statistic = 2,22949
德宾-沃森是 2.22。接近 2。所以这意味着(标准化?)残差是随机且独立分布的?