No. Emp. No. Prod. Wkrs. Value Added by Mfg. Cost of Materials Value of Indus. Shipmnts New Cap. Exp. End Yr. Inven. Indus. Grp. 433 370 23518 78713 4 1833 3630 1 131 83 15724 42774 4 1056 3157 1 204 169 24506 27222 4 1405 8732 1 100 70 21667 37040 4 1912 3407 1 220 137 20712 12030 4 1006 1155 1 89 69 12640 13674 3 873 3613 1 26 18 4258 19130 3 487 1946 1 143 72 35210 33521 4 2011 7199 1
No. Emp. No. Prod. Wkrs. Value Added by Mfg. Cost of Materials Value of Indus. Shipmnts New Cap. Exp. End Yr. Inven. Indus. Grp. 433 370 23518 78713 4 1833 3630 1 131 83 15724 42774 4 1056 3157 1 204 169 24506 27222 4 1405 8732 1 100 70 21667 37040 4 1912 3407 1 220 137 20712 12030 4 1006 1155 1 89 69 12640 13674 3 873 3613 1 26 18 4258 19130 3 487 1946 1 143 72 35210 33521 4 2011 7199 1
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
No. Emp. | No. Prod. Wkrs. | Value Added by Mfg. | Cost of Materials | Value of Indus. Shipmnts | New Cap. Exp. | End Yr. Inven. | Indus. Grp. |
433 | 370 | 23518 | 78713 | 4 | 1833 | 3630 | 1 |
131 | 83 | 15724 | 42774 | 4 | 1056 | 3157 | 1 |
204 | 169 | 24506 | 27222 | 4 | 1405 | 8732 | 1 |
100 | 70 | 21667 | 37040 | 4 | 1912 | 3407 | 1 |
220 | 137 | 20712 | 12030 | 4 | 1006 | 1155 | 1 |
89 | 69 | 12640 | 13674 | 3 | 873 | 3613 | 1 |
26 | 18 | 4258 | 19130 | 3 | 487 | 1946 | 1 |
143 | 72 | 35210 | 33521 | 4 | 2011 | 7199 | 1 |
171 | 126 | 20548 | 19612 | 4 | 1135 | 3135 | 1 |
21 | 15 | 23442 | 5557 | 3 | 605 | 5506 | 2 |
3 | 2 | 287 | 163 | 1 | 2 | 42 | 2 |
2 | 2 | 1508 | 314 | 1 | 15 | 155 | 2 |
6 | 4 | 624 | 2622 | 1 | 27 | 554 | 2 |
52 | 47 | 2471 | 4219 | 2 | 292 | 929 | 3 |
74 | 63 | 4307 | 5357 | 2 | 454 | 1427 | 3 |
13 | 12 | 673 | 1061 | 1 | 20 | 325 | 3 |
17 | 13 | 817 | 707 | 1 | 84 | 267 | 3 |
169 | 147 | 8986 | 10421 | 3 | 534 | 2083 | 3 |
51 | 41 | 3145 | 4140 | 2 | 220 | 697 | 3 |
55 | 44 | 4076 | 7125 | 2 | 176 | 1446 | 3 |
84 | 76 | 3806 | 8994 | 2 | 423 | 1014 | 3 |
61 | 47 | 4276 | 5504 | 2 | 464 | 1291 | 3 |
27 | 22 | 1239 | 716 | 1 | 22 | 356 | 4 |
200 | 178 | 9423 | 8926 | 3 | 200 | 2314 | 4 |
294 | 250 | 11045 | 11121 | 3 | 189 | 2727 | 4 |
38 | 32 | 1916 | 2283 | 1 | 29 | 682 | 4 |
17 | 14 | 599 | 364 | 1 | 21 | 197 | 4 |
34 | 28 | 2063 | 1813 | 1 | 20 | 450 | 4 |
1 | 1 | 34 | 71 | 1 | 2 | 17 | 4 |
31 | 25 | 1445 | 1321 | 1 | 16 | 526 | 4 |
224 | 179 | 10603 | 12376 | 3 | 465 | 2747 | 4 |
83 | 68 | 5775 | 9661 | 3 | 539 | 578 | 5 |
172 | 147 | 10404 | 19285 | 4 | 1071 | 3979 | 5 |
257 | 209 | 13274 | 18632 | 4 | 711 | 3329 | 5 |
51 | 43 | 1909 | 2170 | 1 | 88 | 355 | 5 |
82 | 68 | 4606 | 7290 | 2 | 182 | 580 | 5 |
94 | 78 | 5518 | 8135 | 2 | 715 | 1604 | 5 |
273 | 233 | 12464 | 12980 | 3 | 481 | 3535 | 6 |
70 | 53 | 5447 | 4011 | 2 | 358 | 829 | 6 |
37 | 29 | 2290 | 5101 | 2 | 128 | 447 | 6 |
81 | 61 | 4182 | 3755 | 2 | 177 | 956 | 6 |
54 | 39 | 2818 | 2694 | 2 | 109 | 718 | 6 |
15 | 11 | 2201 | 3279 | 2 | 698 | 725 | 7 |
116 | 90 | 18848 | 20596 | 4 | 3143 | 4257 | 7 |
55 | 42 | 9655 | 10604 | 3 | 2360 | 1502 | 7 |
212 | 163 | 15668 | 24634 | 4 | 1352 | 3976 | 7 |
232 | 182 | 25918 | 28963 | 4 | 1750 | 5427 | 7 |
403 | 136 | 30692 | 8483 | 4 | 1277 | 894 | 8 |
121 | 16 | 17982 | 6940 | 3 | 311 | 1216 | 8 |
136 | 57 | 17857 | 8863 | 3 | 618 | 3736 | 8 |
69 | 25 | 9699 | 2823 | 2 | 144 | 874 | 8 |
604 | 437 | 38407 | 29572 | 4 | 2959 | 4300 | 8 |
41 | 28 | 3878 | 3811 | 2 | 198 | 688 | 8 |
21 | 12 | 3989 | 1047 | 2 | 66 | 577 | 8 |
65 | 50 | 4388 | 2055 | 2 | 130 | 504 | 8 |
55 | 39 | 4055 | 1098 | 2 | 210 | 236 | 8 |
80 | 45 | 16567 | 11298 | 3 | 2002 | 2644 | 9 |
115 | 79 | 25025 | 34596 | 4 | 3731 | 6192 | 9 |
213 | 106 | 59813 | 27187 | 4 | 4301 | 11533 | 9 |
126 | 75 | 31801 | 19932 | 4 | 1304 | 4535 | 9 |
51 | 28 | 8497 | 9849 | 3 | 404 | 2178 | 9 |
126 | 75 | 28886 | 46935 | 4 | 6269 | 8577 | 9 |
37 | 24 | 12277 | 11130 | 3 | 1025 | 2354 | 9 |
76 | 45 | 11547 | 13085 | 3 | 1006 | 2749 | 9 |
67 | 43 | 26006 | 132880 | 4 | 5197 | 10718 | 10 |
25 | 18 | 3464 | 6182 | 2 | 251 | 658 | 10 |
14 | 8 | 2187 | 4446 | 2 | 124 | 670 | 10 |
65 | 54 | 7079 | 7091 | 3 | 579 | 1067 | 11 |
8 | 7 | 442 | 496 | 1 | 9 | 175 | 11 |
61 | 46 | 4528 | 3805 | 2 | 341 | 1057 | 11 |
122 | 95 | 7275 | 7195 | 3 | 435 | 1411 | 11 |
763 | 598 | 55621 | 57264 | 4 | 5658 | 11874 | 11 |
15 | 12 | 1313 | 1865 | 1 | 52 | 404 | 12 |
3 | 2 | 162 | 163 | 1 | 1 | 35 | 12 |
37 | 31 | 1907 | 1682 | 1 | 35 | 716 | 12 |
2 | 2 | 53 | 85 | 1 | 12 | 62 | 12 |
6 | 4 | 747 | 395 | 1 | 18 | 199 | 12 |
8 | 7 | 328 | 255 | 1 | 6 | 75 | 12 |
7 | 6 | 233 | 177 | 1 | 4 | 40 | 12 |
12 | 9 | 1717 | 943 | 1 | 248 | 282 | 13 |
60 | 51 | 6532 | 3527 | 2 | 853 | 1505 | 13 |
64 | 50 | 4850 | 4254 | 2 | 493 | 883 | 13 |
17 | 13 | 3509 | 2282 | 2 | 495 | 828 | 13 |
31 | 25 | 2176 | 1387 | 1 | 201 | 700 | 13 |
45 | 36 | 2696 | 1183 | 1 | 154 | 600 | 13 |
205 | 152 | 15739 | 17010 | 4 | 1200 | 1966 | 13 |
17 | 13 | 999 | 565 | 1 | 50 | 263 | 13 |
72 | 53 | 7838 | 5432 | 2 | 464 | 1652 | 13 |
221 | 174 | 29180 | 45696 | 4 | 3433 | 12198 | 14 |
128 | 106 | 9061 | 6913 | 3 | 651 | 1543 | 14 |
35 | 26 | 4200 | 11184 | 3 | 635 | 1834 | 14 |
15 | 11 | 1410 | 5735 | 2 | 90 | 694 | 14 |
162 | 123 | 16670 | 31892 | 4 | 1761 | 6377 | 14 |
94 | 79 | 5856 | 4696 | 2 | 459 | 938 | 14 |
32 | 23 | 3164 | 2790 | 2 | 271 | 800 | 14 |
33 | 27 | 3999 | 9364 | 2 | 526 | 1453 | 15 |
140 | 107 | 11750 | 8720 | 3 | 620 | 3124 | 15 |
45 | 32 | 4412 | 3527 | 2 | 178 | 1121 | 15 |
432 | 315 | 27974 | 31527 | 4 | 1139 | 7204 | 15 |
104 | 81 | 6936 | 4909 | 2 | 421 | 1768 | 15 |
259 | 211 | 19880 | 21531 | 4 | 1908 | 3997 | 15 |
129 | 99 | 7793 | 6232 | 3 | 724 | 1181 | 15 |
40 | 24 | 3528 | 1689 | 2 | 85 | 1077 | 15 |
300 | 219 | 21718 | 19273 | 4 | 1273 | 6460 | 15 |
79 | 55 | 10513 | 12954 | 3 | 678 | 3679 | 16 |
94 | 70 | 9545 | 11858 | 3 | 414 | 3339 | 16 |
205 | 133 | 18178 | 23474 | 4 | 889 | 7344 | 16 |
295 | 211 | 22673 | 14343 | 4 | 1485 | 6730 | 16 |
192 | 110 | 19221 | 16515 | 4 | 1334 | 6823 | 16 |
265 | 172 | 23110 | 18543 | 4 | 1260 | 7898 | 16 |
259 | 96 | 41135 | 60857 | 4 | 2917 | 10277 | 16 |
201 | 147 | 17521 | 21819 | 4 | 907 | 4857 | 16 |
392 | 293 | 25322 | 13897 | 4 | 1568 | 4964 | 16 |
74 | 51 | 6700 | 5523 | 2 | 308 | 1495 | 17 |
171 | 120 | 14278 | 12657 | 3 | 784 | 3887 | 17 |
108 | 87 | 9466 | 12578 | 3 | 721 | 2299 | 17 |
157 | 117 | 13428 | 11065 | 3 | 671 | 3076 | 17 |
49 | 37 | 3459 | 7621 | 2 | 485 | 1070 | 17 |
258 | 120 | 38705 | 29591 | 4 | 2268 | 9467 | 17 |
588 | 368 | 84059 | 44486 | 4 | 14345 | 13145 | 17 |
151 | 106 | 13920 | 13398 | 3 | 1286 | 3514 | 17 |
772 | 634 | 105899 | 223639 | 4 | 10264 | 15852 | 18 |
377 | 190 | 45220 | 42367 | 4 | 2023 | 36814 | 18 |
141 | 108 | 7903 | 7760 | 3 | 351 | 2165 | 18 |
31 | 23 | 2590 | 4363 | 2 | 97 | 1233 | 18 |
18 | 14 | 1435 | 1674 | 1 | 131 | 412 | 18 |
81 | 29 | 9986 | 8120 | 3 | 490 | 4770 | 18 |
47 | 35 | 3564 | 5476 | 2 | 142 | 1102 | 18 |
186 | 68 | 21071 | 8760 | 4 | 1223 | 6183 | 19 |
272 | 141 | 29028 | 18028 | 4 | 1466 | 7681 | 19 |
268 | 157 | 31051 | 16787 | 4 | 1648 | 7761 | 19 |
27 | 17 | 2390 | 1020 | 1 | 197 | 426 | 19 |
61 | 36 | 14032 | 8114 | 3 | 724 | 2290 | 19 |
6 | 4 | 415 | 382 | 1 | 17 | 177 | 19 |
43 | 30 | 2761 | 3646 | 2 | 119 | 1451 | 20 |
13 | 10 | 685 | 506 | 1 | 15 | 328 | 20 |
103 | 76 | 8327 | 6604 | 3 | 396 | 2608 | 20 |
35 | 26 | 2643 | 1789 | 1 | 197 | 799 | 20 |
24 | 19 | 1406 | 997 | 1 | 51 | 415 | 20 |
179 | 123 | 11199 | 8530 | 3 | 595 | 2861 | 20 |

Transcribed Image Text:Use the Manufacturing database from "Excel Databases.xls" on Blackboard. Use Excel to develop a multiple regression model to predict Cost of Materials by Number of
Employees, New Capital Expenditures, Value Added by Manufacture, and End-of-Year Inventories.
Use Excel to perform a test of the overall model. Write the test statistic. Round your answer to 2 decimal places
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