analysisoflinearregression剖析.ppt

inverse power logistic u is the upper bound value in the formula. 选择要保存的新变量 因变量预测值 残差 预测区间 预测区间的置信度 观测值预测 观测值预测 provide the corresponding forecast of all observation using the last observation time of the data set as its boundary If the forecast range is beyond the last observation time of the data set, we should choose it and type the number forecast in chronological order in the observation frame, then output the corresponding forecast. This frame can conduct the choose when we choose the time as independent variable at the first time. Dependent variable.. Y Method.. LINEAR List wise Deletion of Missing Data Multiple R .84512 R Square .71423 Adjusted R Square .65708 Standard Error 8.67640 Analysis of Variance: DF Sum of Squares Mean Square Regression 1 940.76036 940.76036 Residuals 5 376.39964 75.27993 F = 12.49683 Signif F = .0166 -------------------- Variables in the Equation -------------------- Variable B SE B Beta T Sig T X 5.796429 1.639686 .845124 3.535 .0166 (Constant) 63.314286 7.332897 8.634 .0003 The fit result of linear equation Dependent variable.. Y Method.. LOGARITH List wise Deletion of Missing Data Multiple R .95539 R Square .91277 Adjusted R Square .89532 Standard Error 4.79374 Analysis of Variance: DF Sum of Squares Mean Square Regression 1 1202.2604 1202.2604 Residuals 5 114.8996 22.9799 F = 52.31786 Signif F = .0008 -------------------- Variables in the Equation -------------------- Variable B SE B Beta T Sig T X 20.670405 2.857749 .955388 7.233 .0008 (Constant) 61.325923 3.923774 15.6