Three different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 30 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 10 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: ; . SST=10,800 ; SSTR=4,530 a. Set up the ANOVA table for this problem (to 2 decimals, if necessary). Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value (to 4 decimals) treatment error total B.Use a=.05 to test for any significant difference in the means for the three assembly methods. Calculate the value of the test statistic (to 2 decimals).
Three different methods for assembling a product were proposed by an industrial engineer. To investigate the number of units assembled correctly with each method, 30 employees were randomly selected and randomly assigned to the three proposed methods in such a way that each method was used by 10 workers. The number of units assembled correctly was recorded, and the analysis of variance procedure was applied to the resulting data set. The following results were obtained: ; .
SST=10,800 ; SSTR=4,530
a. Set up the ANOVA table for this problem (to 2 decimals, if necessary).
| Source of Variation | Sum of Squares | Degrees of Freedom | Mean Square | F | p-value (to 4 decimals) |
| treatment | |||||
| error | |||||
| total |
B.Use a=.05 to test for any significant difference in the means for the three assembly methods.
Calculate the value of the test statistic (to 2 decimals).
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