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[求助]
響應(yīng)面的分析問(wèn)題
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Response 1 提取率 ANOVA for Response Surface Quadratic Model Analysis of variance table [Partial sum of squares - Type III] Sum of Mean F p-value Source Squares df Square Value Prob > F Model 5.75 9 0.64 1096.70 < 0.0001 significant A-電機(jī)電壓 1.56 1 1.56 2680.66 < 0.0001 B-提取時(shí)間 1.12 1 1.12 1914.16 < 0.0001 C-料液比 0.49 1 0.49 835.43 < 0.0001 AB 0.027 1 0.027 46.13 0.0011 AC 0.041 1 0.041 69.99 0.0004 BC 0.011 1 0.011 18.20 0.0080 A^2 1.40 1 1.40 2401.77 < 0.0001 B^2 1.02 1 1.02 1751.06 < 0.0001 C^2 0.44 1 0.44 755.23 < 0.0001 Residual 2.915E-003 5 5.830E-004 Lack of Fit 2.547E-003 3 8.488E-004 4.60 0.1836 not significant Pure Error 3.687E-004 2 1.843E-004 Cor Total 5.76 14 The Model F-value of 1096.70 implies the model is significant. There is only a 0.01% chance that a "Model F-Value" this large could occur due to noise. Values of "Prob > F" less than 0.0500 indicate model terms are significant. In this case A, B, C, AB, AC, BC, A++2+-, B++2+-, C++2+- are significant model terms. Values greater than 0.1000 indicate the model terms are not significant. If there are many insignificant model terms (not counting those required to support hierarchy), model reduction may improve your model. The "Lack of Fit F-value" of 4.60 implies the Lack of Fit is not significant relative to the pure error. There is a 18.36% chance that a "Lack of Fit F-value" this large could occur due to noise. Non-significant lack of fit is good -- we want the model to fit. Std. Dev. 0.024 R-Squared 0.9995 Mean 5.17 Adj R-Squared 0.9986 C.V. % 0.47 Pred R-Squared 0.9928 PRESS 0.042 Adeq Precision 95.113 發(fā)自小木蟲(chóng)Android客戶端 |
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