第五章回归分析方法 Regression Anal ysis: y versus x The regression equation is y=28.1+133x Predictor Coef SE Coef T P cmese, uestc: Constant 28.083 1.567 17.920.000 132.899 9.606 13.830.000 s=1.309 R-Sq=95.0% R-Sq(adj)=94.5% Anal is of var iance Se our ce SS MS F Regression 327.93 32793191.400.000 Residua error 10 17.13 1.71 Total 345.06 Schodl of microelectronics and Solid-State Electronics 26
School of Microelectronics and Solid-State Electronics 26 第五章 回归分析方法 Regression Analysis: y versus x The regression equation is y = 28.1 + 133 x Predictor Coef SE Coef T P Constant 28.083 1.567 17.92 0.000 x 132.899 9.606 13.83 0.000 S = 1.309 R-Sq = 95.0% R-Sq(adj) = 94.5% Analysis of Variance Source DF SS MS F P Regression 1 327.93 327.93 191.40 0.000 Residual Error 10 17.13 1.71 Total 11 345.06
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School of Microelectronics and Solid-State Electronics 27 第五章 回归分析方法
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School of Microelectronics and Solid-State Electronics 28 第五章 回归分析方法
第五章回归分析方法 l Es OriginPro 7.5-C: \Documents and Settings\Adinistrator\Appl 回 File Edit View Graph Data Analysis Tools Format Window Help 幽圖回国回圆囝囝喝回鳅回应凵叫叫 幽幽崛倒酬司曷回圆时 叫叫■可 Fal目 GraphI 区 ar Fit of Data 1 B cmese uestc: ⊙公C LInear Regression for Data1 B V=+B“X Parameter Ualue Error 28.68259 1.56721 132.899469.66618 N .97486 1.3893 <目.81 Color Publication 1: Datal_B(1-12) Schodl of microelectronics and Solid-State Electronics
School of Microelectronics and Solid-State Electronics 29 第五章 回归分析方法
第五章回归分析方法 回归方程是否有意义的判断 在使用回归方程作进一步的分析以前,首先 应对回归方程是否有意义进行判断。 cmese, uestc: 三种等价的检验方法 F检验 T检验 检验 Schodl of microelectronics and Solid-State Electronics
School of Microelectronics and Solid-State Electronics 30 第五章 回归分析方法 回归方程是否有意义的判断 三种等价的检验方法 – F 检验 – T检验 – r检验 在使用回归方程作进一步的分析以前，首先 应对回归方程是否有意义进行判断