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[求助]
響應(yīng)面結(jié)果分析 已有1人參與
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響應(yīng)面顯著性分析結(jié)果如下: Sum of Mean F p-value Source Squares df Square Value Prob > F Model 791.13 6 131.86 4.01 0.0262 significant A-P 194.37 1 194.37 5.91 0.0353 B-t 93.57 1 93.57 2.85 0.1224 C-C 134.10 1 134.10 4.08 0.0710 AB 170.56 1 170.56 5.19 0.0459 AC 146.98 1 146.98 4.47 0.0606 BC 51.55 1 51.55 1.57 0.2389 Residual 328.64 10 32.86 Lack of Fit 247.33 6 41.22 2.03 0.2573 not significant Pure Error 81.31 4 20.33 Cor Total 1119.77 16 The Model F-value of 4.01 implies the model is significant. There is only a 2.62% 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, AB 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 2.03 implies the Lack of Fit is not significant relative to the pure error. There is a 25.73% 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. 模型顯著,失擬不顯著,A、AB顯著,其余項(xiàng)不顯著,那回歸方程還是顯著嗎?模型有沒有問題?謝謝! |
Environstudies |
木蟲 (正式寫手)
木蟲 (正式寫手)
| Model was significant, Lack of Fit was not significant,說(shuō)明你的模型是可以的,即回歸方程是可以的,但是你的因子只有3個(gè),而且只有一個(gè)是顯著的,互作里面也只有一個(gè)是顯著的,要是想拿此來(lái)發(fā)文章估計(jì)困難。前幾年響應(yīng)面類的實(shí)驗(yàn)挺風(fēng)火,近2年已呈現(xiàn)疲軟趨勢(shì),新異性不是很大了。祝順利。 |
金蟲 (小有名氣)
銅蟲 (小有名氣)
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