An air-conditioning repair department manager has compiled data on the primary reason for 41 service calls for the previous week, as shown in the table. Job Number Problem/ Customer Type Job Number Problem/ Customer Type Job Number Problem/ Customer Type 301 O/C 315 W/R 329 N/C 302 N/C 316 F/R 330 O/R 303 F/R 317 F/R 331 N/R 304 O/R 318 N/R 332 W/C 305 F/R 319 F/R 333 W/C 306 N/R 320 N/R 334 N/R 307 N/C 321 O/C 335 F/C 308 O/R 322 W/C 336 W/C 309 N/R 323 F/R 337 F/C 310 N/C 324 O/C 338 N/R 311 O/C 325 W/C 339 N/R 312 O/R 326 N/C 340 N/C 313 N/R 327 O/R 341 N/R 314 O/R 328 N/R Key: Problem type: Customer type: N = Noisy C = Commercial customer F = Equipment failure R = Residential customer W = Runs warm O = Odor Problem 9-2 Part a a. Using the data, prepare a check sheet for the problem types for each customer type. (1) Residential customer type Residential Noisy Failed Odor Warm Totals (2) Commercial customer type Commercial Odor Failed Noisy Warm Totals
An air-conditioning repair department manager has compiled data on the primary reason for 41 service calls for the previous week, as shown in the table. Job Number Problem/ Customer Type Job Number Problem/ Customer Type Job Number Problem/ Customer Type 301 O/C 315 W/R 329 N/C 302 N/C 316 F/R 330 O/R 303 F/R 317 F/R 331 N/R 304 O/R 318 N/R 332 W/C 305 F/R 319 F/R 333 W/C 306 N/R 320 N/R 334 N/R 307 N/C 321 O/C 335 F/C 308 O/R 322 W/C 336 W/C 309 N/R 323 F/R 337 F/C 310 N/C 324 O/C 338 N/R 311 O/C 325 W/C 339 N/R 312 O/R 326 N/C 340 N/C 313 N/R 327 O/R 341 N/R 314 O/R 328 N/R Key: Problem type: Customer type: N = Noisy C = Commercial customer F = Equipment failure R = Residential customer W = Runs warm O = Odor Problem 9-2 Part a a. Using the data, prepare a check sheet for the problem types for each customer type. (1) Residential customer type Residential Noisy Failed Odor Warm Totals (2) Commercial customer type Commercial Odor Failed Noisy Warm Totals
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Problem 9-2
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An air-conditioning repair department manager has compiled data on the primary reason for 41 service calls for the previous week, as shown in the table. |
Job Number |
Problem/ Customer Type |
Job Number |
Problem/ Customer Type |
Job Number |
Problem/ Customer Type |
301 | O/C | 315 | W/R | 329 | N/C |
302 | N/C | 316 | F/R | 330 | O/R |
303 | F/R | 317 | F/R | 331 | N/R |
304 | O/R | 318 | N/R | 332 | W/C |
305 | F/R | 319 | F/R | 333 | W/C |
306 | N/R | 320 | N/R | 334 | N/R |
307 | N/C | 321 | O/C | 335 | F/C |
308 | O/R | 322 | W/C | 336 | W/C |
309 | N/R | 323 | F/R | 337 | F/C |
310 | N/C | 324 | O/C | 338 | N/R |
311 | O/C | 325 | W/C | 339 | N/R |
312 | O/R | 326 | N/C | 340 | N/C |
313 | N/R | 327 | O/R | 341 | N/R |
314 | O/R | 328 | N/R | ||
Key: | Problem type: | Customer type: | ||
N | = Noisy | C | = Commercial customer | |
F | = Equipment failure | R | = Residential customer | |
W | = Runs warm | |||
O | = Odor | |||
Problem 9-2 Part a
a. | Using the data, prepare a check sheet for the problem types for each customer type. |
(1) | Residential customer type |
Residential | |
Noisy | |
Failed | |
Odor | |
Warm | |
Totals | |
(2) | Commercial customer type |
Commercial | |
Odor | |
Failed | |
Noisy | |
Warm | |
Totals | |
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