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The aim is to investigate the influence of the carbon content C. [%) (C, C) and the casting temperature TC) (T), T, T and Tato have the number of defective parts in a mold. The following ANOVA table was calculated (significance level 5%). Indicate what type of analysis of variance it is. Explain your decision. Test the given hypotheses and interpret the results. Specify the effect sizes. ANOVA table: Causes of dispersion Sums of squares df P value Carbon content 0.43 1 0.7181 Casting temperature 56.04 3 0.0187 interaction 22.78 3 0.0405 failure 97.82 32 total 177.07 39 Name of the test procedure: O One-way analysis of variance with repeated measurements O Two-factor analysis of variance without repetition of measurements O Two-factor analysis of variance with repeated measures O h-test according to Kruskal and Wallis Reason: O There are three influencing factors O There are two influencing factors and how they interact O The ANOVA table lists the error hypothesis H3 discard: Interpretation: O There are no very significant errors O There are significant interactions

The aim is to investigate the influence of the carbon content C. [%) (C, C) and the casting temperature TC) (T), T, T and Tato have the number of defective parts in a mold. The following ANOVA table was calculated (significance level 5%). Indicate what type of analysis of variance it is. Explain your decision. Test the given hypotheses and interpret the results. Specify the effect sizes. ANOVA table: Causes of dispersion Sums of squares df P value Carbon content 0.43 1 0.7181 Casting temperature 56.04 3 0.0187 interaction 22.78 3 0.0405 failure 97.82 32 total 177.07 39 Name of the test procedure: O One-way analysis of variance with repeated measurements O Two-factor analysis of variance without repetition of measurements O Two-factor analysis of variance with repeated measures O h-test according to Kruskal and Wallis Reason: O There are three influencing factors O There are two influencing factors and how they interact O The ANOVA table lists the error hypothesis H3 discard: Interpretation: O There are no very significant errors O There are significant interactions

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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The aim is to investigate the influence of the carbon content C. [%) (C, C,) and the casting temperature T [°C) (T), T, Tỷ and Tuhto have the number of defective parts in a mold. The following ANOVA table was calculated (significance level 5%). Indicate what type of analysis of variance it is. Explain your decision. Test the given hypotheses and interpret the results. Specify the effect sizes. ANOVA table: Causes of dispersion Sums of squares dfP value Carbon content 0.43 0.7181 Casting temperature 56.04 0.0187 interaction 22.78 3 0.0405 failure 97.82 32 total 177.07 39 Name of the test procedure: O One-way analysis of variance with repeated measurements O Two-factor analysis of variance without repetition of measurements O Two-factor analysis of variance with repeated measures O h-test according to Kruskal and Wallis Reason: O There are three influencing factors O There are two influencing factors and how they interact O The ANOVA table lists the error hypothesis H3 discard: Interpretation: O There are no very significant errors O There are significant interactions O There are very significant interactions
Transcribed Image Text:The aim is to investigate the influence of the carbon content C. [%) (C, C,) and the casting temperature T [°C) (T), T, Tỷ and Tuhto have the number of defective parts in a mold. The following ANOVA table was calculated (significance level 5%). Indicate what type of analysis of variance it is. Explain your decision. Test the given hypotheses and interpret the results. Specify the effect sizes. ANOVA table: Causes of dispersion Sums of squares dfP value Carbon content 0.43 0.7181 Casting temperature 56.04 0.0187 interaction 22.78 3 0.0405 failure 97.82 32 total 177.07 39 Name of the test procedure: O One-way analysis of variance with repeated measurements O Two-factor analysis of variance without repetition of measurements O Two-factor analysis of variance with repeated measures O h-test according to Kruskal and Wallis Reason: O There are three influencing factors O There are two influencing factors and how they interact O The ANOVA table lists the error hypothesis H3 discard: Interpretation: O There are no very significant errors O There are significant interactions O There are very significant interactions
hypothesis H, discard: Interpretation: O There are no very significant differences in the interaction O There are significant differences in carbon content O There are very significant differences in carbon content O There are no significant differences in terms of carbon content Effect strength carbon content: (土0.00) Effect strength casting temperature: (土0.00) Effect size interaction: (土 0.00) Overall hypothesis H discard: Analysis: O The casting temperature can explain about 31.65% of the errors that occur O Approx. 31.65% of the errors that occur can be explained by interactions O About 31.65% of the errors that occur can be explained by the carbon content Comment:
Transcribed Image Text:hypothesis H, discard: Interpretation: O There are no very significant differences in the interaction O There are significant differences in carbon content O There are very significant differences in carbon content O There are no significant differences in terms of carbon content Effect strength carbon content: (土0.00) Effect strength casting temperature: (土0.00) Effect size interaction: (土 0.00) Overall hypothesis H discard: Analysis: O The casting temperature can explain about 31.65% of the errors that occur O Approx. 31.65% of the errors that occur can be explained by interactions O About 31.65% of the errors that occur can be explained by the carbon content Comment:
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Two Way ANOVA  

ANOVA Stands For Analysis of variance and tests for differences in the effects of independent variables on a dependent variable . A two - way ANOVA test is a statistical test to determine the effect of two nominal  predictor variables on a continuous variable 

 

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