【正文】 esuretostoreyourdesigninaworksheet…、 StatDOE63Minitab2KDOEWorksheet、 StatDOE64Minitab1. Enter Response2. Identify the Terms to include in the model. Initially include all factors and interactions. 、 StatDOE2KDOEAnalyze65Minitab3. Click on the Graphs button so we can review the Normal probability plot of the Effects4. Identify the Normal and Pareto plots. The default value of Alpha in Minitab 14 is .、 StatDOE2KDOEAnalyze66MinitabThese are the contrasts you previously calculatedNotice there are no Fvalues or Pvalues because there is only one measurement in each cell and the error term can not be calculated.、 StatDOE2KDOEAnalyze67MinitabWe see here that the Effects associated with A(Temp) and the A*C (Temperature * Chip) Interaction are important. So we will evaluate the highest order interaction and not worry about the Main Effect.、 StatDOE2KDOEAnalyze68MinitabThis chart pareto’s the effects and uses a p as a cutoffYou can see that the A and A*C interactions are identified as good candidatesWe can also reduce the model by removing the ABC interaction and get some analytical basis、 StatDOE2KDOEAnalyze69Minitab? But what is the basis for the ‘red line’?– The Ho is that there are no significant effects (none of the terms are significant)– Therefore, we would expect the Effects to be 0 to support the Ho– The red line is a confidence limit based on our Alpha level that establishes a basis for saying ‘Anything beyond that limit is different than 0’? The calculation of the line is based on a few factors:– Experimental error– a level– Total number of runs in the experiment– Degrees of Freedom? As we reduce the model, the position of the line will also change!、 StatDOE2KDOEAnalyze70Minitab? 去掉三因子的交互作用 ABC進行重復(fù)分析? 將有足夠的自由度來得到誤差項并給出 P值 !、 StatDOE2KDOE－ ReducedModel71MinitabNow we can reduce the model more by removing the interactions that are significantly above our a value of Remove theseinteractions、 StatDOE2KDOE－ ReducedModel72Minitab、 StatDOE2KDOE－ ReducedModel73Minitab、 StatDOE2KDOE－ ReducedModel74MinitabIdentify the response variable and the terms to include in the interactions plot、 StatDOE2KDOE－ ReducedModel75Minitab我們可以運用主效果圖分析單因子的效果，用交互作用圖來分析 Temperature 和 Chip 之間的交互作用、 StatDOE2KDOE－ ReducedModel76MinitabRating = + (Temp) (Time) + (Chip) + (T*Ti) + (T*C) + (Ti*C) + (T*Ti*C)我們可以從 ANOVA 分析出的因子系數(shù)得出如下的數(shù)學(xué)模型 :Note: The above equation is in terms of coded (177。1) levels 我們使用僅有顯著因子的精簡模型 :當(dāng)所有因子都為高水平時 (+1)，計算 Rating 的值為多少？Rating = + (Temp) (Time) + (Chip) + (T*C)MathematicalModel、 StatDOE77MinitabResponseOptimize、 StatDOE78MinitabResponse Optimization Parameters Goal Lower Target Upper Weight ImportRating Target 50 70 90 1 1Global SolutionTemp = Time = Chip = 1 (1)Predicted ResponsesRating = 70 , desirability = Composite Desirability = 、 StatDOEResponseOptimize79Minitab WrapUp80MinitabHypothesisTestingofMeansRoadmap3 or more factorsComparing Means1 Factor1sample ZtestTwo way ANOVA ANOVAGLMOne way ANOVA1sample ttest2samplettestPaired ttest1 Sample 2 Samples 2 or more samples2 Factorss not knowns known independent paired81Minitab1VarianceTest1SampleComparing Variances2VarianceTest2SampleTestforEqualVarianceMoreThan2SamplesLevene’sTestBartlett’sTestLevene’sTestFTestDescriptiveStatisticsHypothesisTestingofMeansRoadmap82Minitab1 ProportionTestComparing ProportionsHypothesisTestingofProportionRoadmap2 ProportionTest2 SampleChiSquare TestMore than 2 samples1 Sample83MinitabWhentoUseANOVAVariables Road Map1Samplettest1Sample2SamplettestPairedComparisonsTukey39。sQuickTest2SamplesANOVA2ormoresamplesVariables Data1 Mean 2 Means 2+ MeansANOVA is used to test two or more means84MinitabAnyQuestion?85Minitab謝謝觀看 /歡迎下載BY FAITH I MEAN A VISION OF GOOD ONE CHERISHES AND THE ENTHUSIASM THAT PUSHES ONE TO SEEK ITS FULFILLMENT REGARDLESS OF OBSTACLES. BY FAITH I BY FAIT