i Safari Autc Home lam Clipboard Insert SUMMARV im III blw'N Hi ANOVA 7 Source of Va Rows Columns Error Total File Edit View History Bookmarks Window Help '3 l4) 'r? Q A Sat Sep 18 7157 PM o T O O . EC U 3 0 E B ng.cengage.com 6 @ U + la Student Portal | Asnrord University A Week 4 - Assignment A Week 4 MindTap ANOVA a: MindTap - Cengage Learning 'IICENGAGE i MINDTAP Q Search this course 0 13.1 Excel Activity 1 ANOVA (Structured) 0 X Question 1 3313/10 A manufacturing company has been selected to assemble a small but important component that will be used during the construction of numerous infrastructure projects. The company anticipates the need to assemble several million components over the next several years. Company engineers select three potential assembly methods: Method A, Method B, and Method C. Management would like to select the method that produces the fewest number parts per 10,000 parts produced that do not meet specications. It may also be possible that there is no statistical difference between the three methods in which case the lowest cost method will be selected for production. While all parts are checked before leaving the factory, the best method will reduce the number of parts that need to be recycled back into the production process. To test each method, six batches of 10,000 components are produced using each of the three methods. The number of components out of specification are recorded in the Microsoft Excel Online le below. Analyze the data to determine if there is any difference in the mean number of components that are out of specicaion among the three methods. After conducting the analysis report the ndings to the management team. Open spreadsheet a. Compute the sum of squares between treatments (assembly methods). l 1924 0 b. Compute the mean square between treatments (to 1 decimal if necessary). l 962 0 c. Compute the sum of squares due to error. l' 29220 d Compute the mean square due to error (to 1 decimal if necessary). l 194.3 0 e. Set up the ANOVA table for this problem. Round all sum of squares to the nearest whole number. Round all Mean Squares to one decimal place. Round Fto rum AMam-u are\"... Autosaved at 7:57 PM Safari File Edit View History Bookmarks Window Help Co Q 8 Sat Sep 18 7:57 PM Uh RO Q= C OU+ ing Excel template - Saved Search (Option + Q) course ? File Home Insert Draw Page Layout Formulas Data Review View Help Editing Comments X 1 v [ v Arial 10 B Av ... ab General 00 .00 HV ... V E33 fx C D F G H K M ANOVA Completely Randomized Design Batch Method A Method B Method C 163 147 123 142 157 121 DO VOUTAWNY 168 128 136 145 147 143 149 134 152 169 139 129 Formulas 10 Sample Size 6 6 6 Sample Size =COUNT(B3:B8) =COUNT(C3:C8) =COUNT(D3:D8) Sum 936 852 804 Sum =SUM(B3:B8) =SUM(C3:C8) =SUM(D3:D8) 12 Sample Mean 156 142 134 Sample Mean AVERAGE(B3:B8) =AVERAGE(C3:C8) =AVERAGE(D3:D8) A-Z 13 Sample Variance 145.6 108.8 144.8 Sample Variance =VAR.S(B3:B8) =VAR.S(C3:C8) =VAR.S(D3:D8) 14 Sample Standard Deviation 12.0664825 10.43072385 12.03328717 Sample Standard Deviation ESTDEV.S(B3:B8) STDEV.S(C3:8) =STDEV.S(D3:D8) 15 16 Grand Mean 144 Grand Mean (B12+C12+D12)/3 17 ( Office Group Count Group Count #N/A 18 Observation Count Observation Count #NIA 19 20 Source of Variation Sum of Squares Mean Square p-value Source of Variation Sum of Squares df Mean Square F p-value 21 Treatments (Methods) Treatment #N/A #N/A #N/A #N/A #N/A 22 Error Error #NIA #N/A #N/A 23 Tota Total #N/A 24 25 Level of significance 0.05 Level of significance 0 05 26 Reject null? Reject null? #N/A 27 Are the means equal? Are the means equal? #N/A 28 29 30 31 33 34 35 36 At E Sheet1 + xt O Calculation Mode: Automatic Workbook Statistics Give Feedback to Microsoft - 70% +