Consider the experimental results for the following randomized block design. Make the calculations necessary to set up the analysis of variance table. Treatment Blocks Error Total The p-value is-Select your answer - What is your conclusion? - Select your answer- 15 18 5 8 8 8 Use α = 0.05 to test for any significant differences. Show entries to 2 decimals but p-value to 4 decimals, if necessary. Round all intermediate values to two decimal places in your calculations. If your answer is zero enter "0". Source of Variation Sum of Squares Degrees of Freedom Mean Square p-value Treatments F 1 2 3 4 Blocks A 10 12 18 21 B 9 7 с 9 6 14 19

Consider the experimental results for the following randomized block design. Make the calculations necessary to set up the analysis of variance table. Treatment Blocks Error Total The p-value is-Select your answer - What is your conclusion? - Select your answer- 15 18 5 8 8 8 Use α = 0.05 to test for any significant differences. Show entries to 2 decimals but p-value to 4 decimals, if necessary. Round all intermediate values to two decimal places in your calculations. If your answer is zero enter "0". Source of Variation Sum of Squares Degrees of Freedom Mean Square p-value Treatments F 1 2 3 4 Blocks A 10 12 18 21 B 9 7 с 9 6 14 19

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A milk processing company test implemented a plant-wide energy conservation program with a goal of reducing the mean daily consumption rate of at least 1,000 kWh from its normal operating plants. The conservation program was implemented in Plant B. The following data was collected on weekdays where consumption level is at its peak. Were the conservation efforts effective in achieving its goal? Compare the results with Plant A’s data where the program is not implemented using α= 0.05. Assume that the population variances are not equal.
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 =4540. a. Set up the ANOVA table for this problem (to 2 decimals but p-value to 4 decimals, if necessary). Source of Variation Sum of Squares Degrees of Freedom Mean Square F Treatments Error Total 000 The p-value is - Select your answer - What is your conclusion? - Select your answer - p-value b.Use a = 0.05 to test for any significant difference in the means for the three assembly methods. Calculate the value of the test statistic (to 2 decimals).
Explain the circumstances under which we would need to pool the variance for an independent samples t-test
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 tothe resulting data set. The following results were obtained: SST = 10,800; SSTR = 4560.a. Set up the ANOVA table for this problem.b. Use α = .05 to test for any significant difference in the means for the three assembly methods.
A milk processing company test implemented a plant-wide energy conservation program with a goal of reducing the mean daily consumption rate of at least 1,000 kWh from its normal operating plants. The conservation program was implemented in Plant B. The following data was collected on weekdays where consumption level is at its peak. Were the conservation efforts effective in achieving its goal? Compare the results with Plant A’s data where the program is not implemented using � = 0.05. Assume that the population variances are not equal.Plant A (kWh) Plant B (kWh)3,952.80 4,036.003,276.00 4,036.003,636.00 4,036.003,636.00 3,264.003,636.00 864.003,636.00 1,368.004,068.00 2,196.004,068.00 4,392.004,362.00 5,220.004,362.00 3,600.004,362.00 3,960.004,362.00 4,428.003,882.00 756.003,808.80 612.003,808.80 684.00
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 by10 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:10,700 SSTR:4500 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) Treatments…
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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 employeeswere randomly selected and randomly assigned to the three proposed methods in such away that each method was used by 10 workers. The number of units assembled correctlywas recorded, and the analysis of variance procedure was applied to the resulting data set.The following results were obtained: SST = 10,800; SSTR = 4560.a. Set up the ANOVA table for this problem.b. Use a = .05 to test for any significant difference in the means for the three assemblymethods.