You will construct each control chart manually and will be submitted through File Response. You can use Minitab to verify your results, but you have to send the written calculations. Also, perform the Process Capability Analysis assuming the number of opportunities for defects to be 7. Month Orders Orders with error P = orders with error/orders Total errors in all orders U = total errors/ orders Random Sample of Orders Sample orders with errors. Random sample of 1001 Sample errors (number of defects in the Defective orders) 225 49 0.21777778 78 0.34667 100 30 25 378 20 0.05291005 63 0.16667 100 47 25 January February March April May 196 50 0.25510204 65 0.33163 100 20 9 268 24 0.08955224 60 0.22388 100 33 33 283 34 0.12014134 52 0.18375 100 31 40 June 284 49 0.17253521 62 0.21831 100 32 39 183 44 0.24043716 72 0.39344 100 35 39 17 0.06071429 84 280 0.3 100 July August September 42 42 47 0.23152709 64 203 0.31527 100 34 42 0.21674877 October 203 44 41 0.20197 100 8 29 61 377 17 0.04509284 0.1618 100 27 15 November 100 7 December 238 0.08823529 0.39076 31 21 93 0.25497 795 1200 370 Sum 416 345 3118 You will construct each control chart manually and will be submitted through File Response. You can use Minitab to verify your results, but you have to send the written calculations. Also, perform the Process Capability Analysis assuming the number of opportunities for defects to be 7. Month Orders Orders with error P = orders with error/orders Total errors in all orders U = total errors/ orders Random Sample of Orders Sample orders with errors. Random sample of 1001 Sample errors (number of defects in the Defective orders) 225 49 0.21777778 78 0.34667 100 30 25 378 20 0.05291005 63 0.16667 100 47 25 January February March April May 196 50 0.25510204 65 0.33163 100 20 9 268 24 0.08955224 60 0.22388 100 33 33 283 34 0.12014134 52 0.18375 100 31 40 June 284 49 0.17253521 62 0.21831 100 32 39 183 44 0.24043716 72 0.39344 100 35 39 17 0.06071429 84 280 0.3 100 July August September 42 42 47 0.23152709 64 203 0.31527 100 34 42 0.21674877 October 203 44 41 0.20197 100 8 29 61 377 17 0.04509284 0.1618 100 27 15 November 100 7 December 238 0.08823529 0.39076 31 21 93 0.25497 795 1200 370 Sum 416 345 3118