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A second course in statistics regression analysis 7th by mendenhall ch12

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A second course in statistics regression analysis 7th by mendenhall ch12

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Chapter 12 The Analysis of Variance for Designed Experiments Copyright © 2012 Pearson Education, Inc All rights reserved Section 12.1 Introduction Copyright © 2012 Pearson Education, Inc All rights reserved Section 12.2 The Logic Behind an Analysis of Variance Copyright © 2012 Pearson Education, Inc All rights reserved Figure 12.1 Plots of data for two samples Copyright © 2012 Pearson Education, Inc 11- Figure 12.2 Plots of data for two cases Copyright © 2012 Pearson Education, Inc 11- Section 12.3 One-Factor Completely Randomized Designs Copyright © 2012 Pearson Education, Inc All rights reserved Figure 12.3 MINITAB Random assignments of workers to training programs Copyright © 2012 Pearson Education, Inc 11- Figure 12.4 Layout for a completely randomized design Copyright © 2012 Pearson Education, Inc 11- Copyright © 2012 Pearson Education, Inc 11- Copyright © 2012 Pearson Education, Inc 11- Copyright © 2012 Pearson Education, Inc 11- Section 12.8 Other Multiple Comparisons Methods (Optional) Copyright © 2012 Pearson Education, Inc All rights reserved Copyright © 2012 Pearson Education, Inc 11- Copyright © 2012 Pearson Education, Inc 11- ´ Figure 12.27 SAS printout of Scheffe’s multiple comparisons of GPA means, Example 12.22 Copyright © 2012 Pearson Education, Inc 11- Copyright © 2012 Pearson Education, Inc 11- Copyright © 2012 Pearson Education, Inc 11- Figure 12.28 SAS printout of Bonferroni’s multiple comparisons of GPA means, Example 12.23 Copyright © 2012 Pearson Education, Inc 11- Section 12.9 Checking ANOVA Assumptions Copyright © 2012 Pearson Education, Inc All rights reserved Copyright © 2012 Pearson Education, Inc 11- Copyright © 2012 Pearson Education, Inc 11- Figure 12.29 MINITAB histogram for all the GPAs in the completely randomized design Copyright © 2012 Pearson Education, Inc 11- Figure 12.30 MINITAB normal probability plot and normality test for all the GPAs in the completely randomized design Copyright © 2012 Pearson Education, Inc 11- Figure 12.31 MINITAB dot plots for the GPAs in the completely randomized design, by treatment group Copyright © 2012 Pearson Education, Inc 11- Figure 12.32 MINITAB printout of tests for homogeneity of GPA variances for the completely randomized design Copyright © 2012 Pearson Education, Inc 11- ... 2012 Pearson Education, Inc All rights reserved Figure 12.3 MINITAB Random assignments of workers to training programs Copyright © 2012 Pearson Education, Inc 11- Figure 12.4 Layout for a completely...Section 12.1 Introduction Copyright © 2012 Pearson Education, Inc All rights reserved Section 12.2 The Logic Behind an Analysis of Variance Copyright © 2012 Pearson Education, Inc All rights reserved... Education, Inc 11- Figure 12.7 Partitioning of SS(Total) for a completely randomized design Copyright © 2012 Pearson Education, Inc 11- Figure 12.8 MINITAB ANOVA printout for the completely randomized

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Mục lục

  • Figure 12.1 Plots of data for two samples

  • Figure 12.2 Plots of data for two cases

  • Figure 12.3 MINITAB Random assignments of workers to training programs

  • Figure 12.4 Layout for a completely randomized design

  • Figure 12.7 Partitioning of SS(Total) for a completely randomized design

  • Figure 12.9 General form of a randomized block design (treatment is denoted by Tp)

  • Figure 12.11 SAS regression printout for randomized block design reduced model for testing treatments

  • Figure 12.12 SAS regression printout for randomized block design reduced model for testing blocks

  • Figure 12.13 Partitioning of the total sum of squares for the randomized block design

  • Figure 12.14 SPSS ANOVA printout for randomized block design

  • Figure 12.15 Hypothetical plot of the means for the six machine-material combinations

  • Figure 12.16 Testing guidelines for a two-factor factorial experiment

  • Figure 12.17a SAS regression printout for complete factorial model

  • Figure 12.17b SAS regression printout for reduced (main effects) factorial model

  • Figure 12.18 Partitioning of the total sum of squares for a complete two-factor factorial experiment

  • Figure 12.19a SAS ANOVA printout for complete factorial design

  • Figure 12.19b MINITAB plot of profit means illustrating interaction

  • Figure 12.20 SAS regression printout for complete factorial model with quantitative main effects

  • Figure 12.21 SAS regression printout for reduced (second-order) factorial model

  • Figure 12.22 SAS printout of confidence intervals for reduced (second-order) factorial model

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