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zhanghuifeng½ð³æ (ÕýʽдÊÖ)
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±í´ïÁ¿·ÖÎö Term Effect SumSqr % Contribtn Require Intercept Error A-Ethanolamine -1.429 10.2102 0.807924 Error B-Sodium Selenite 0.983 4.83145 0.382308 Model C-Putrescine 15.263 1164.8 92.1692 Error D-EGF 0.209 0.218405 0.0172822 Error E-Lipid Mixture 0.933 4.35245 0.344405 Error F-Sodium Pyruvate 1.733 15.0164 1.18824 Error G-Ascorbic Acid 1.115 6.21613 0.491876 Error H-Glutathione -0.921 4.2412 0.335603 Error J-Dummy1 0.393 0.772245 0.061107 Error K-Choline chloride 1.231 7.5768 0.599546 ErrorL-D-Calcium pantothenate 0.159 0.126405 0.0100023 Error M-Folic Acid 1.377 9.48064 0.750195 Error N-Niacinamide 0.423 0.894645 0.0707924 ErrorO-Pyridoxine hydrochloride -0.363 0.658845 0.0521338 Error P-Riboflavin -0.501 1.25501 0.0993074 ErrorQ-Thiamine hydrochloride -0.239 0.285605 0.0225997 Error R-Vitamin B12 -1.229 7.5522 0.597599 Error S-i-Inositol -2.103 22.113 1.74979 Error T-Dummy2 -0.795 3.16012 0.250058 Lenth's ME 3.35949 Lenth's SME 6.62219 Use your mouse to right click on individual cells for definitions. Response 2 abn ANOVA for selected factorial 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 1164.80 1 1164.80 211.86 < 0.0001 significant C-Putrescine 1164.80 1 1164.80 211.86 < 0.0001 Residual 98.96 18 5.50 Cor Total 1263.76 19 The Model F-value of 211.86 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 C 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. Std. Dev. 2.34 R-Squared 0.9217 Mean 14.04 Adj R-Squared 0.9173 C.V. % 16.70 Pred R-Squared 0.9033 PRESS 122.18 Adeq Precision 20.585 The "Pred R-Squared" of 0.9033 is in reasonable agreement with the "Adj R-Squared" of 0.9173. "Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. Your ratio of 20.585 indicates an adequate signal. This model can be used to navigate the design space. Coefficient Standard 95% CI 95% CI Factor Estimate df Error Low High VIF Intercept 14.04 1 0.52 12.94 15.14 C-Putrescine 7.63 1 0.52 6.53 8.73 1.00 Final Equation in Terms of Coded Factors: abn = +14.04 +7.63 * C Final Equation in Terms of Actual Factors: abn = +6.40800 +47.69687 * Putrescine The Diagnostics Case Statistics Report has been moved to the Diagnostics Node. In the Diagnostics Node, Select Case Statistics from the View Menu. Proceed to Diagnostic Plots (the next icon in progression). Be sure to look at the: 1) Normal probability plot of the studentized residuals to check for normality of residuals. 2) Studentized residuals versus predicted values to check for constant error. 3) Externally Studentized Residuals to look for outliers, i.e., influential values. 4) Box-Cox plot for power transformations. If all the model statistics and diagnostic plots are OK, finish up with the Model Graphs icon. |
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