Use MS excel and the given data to estimate the least squares multiple linear regression model defined by: E(y) = B0 + B1x1 + 62x2 + B3x3 + B4x4+ B5x5

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
6th Edition
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter5: A Survey Of Other Common Functions
Section5.6: Higher-degree Polynomials And Rational Functions
Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...
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Draw a sample of 36 observations from the given data set (in Table 1) below, the 36 observations to be included must start from the observation shown.

X1
X4
X2
X3
X5
Y
16630 15 1232 571 19 |11726
7900 15.6|1077 482 47 |11252
5100 10 963 485 123 12449
5160 12.3 1135 542 144 11030
3600 12.6 1113 534 295 10787
3000 12.3 1124 541 410 10603
3000 14.2 1204 553 515 10144
14000 15.9 1177 521 27 11674
3660 14.6|1135526 56 11510
5400 15.3 1149 514 172 10946
3600 14.2 1141 526 362 10508
3600| 11 |1149 544 354 10604
3600 14.2|1177 525 378 10270
3000 14.2|1116|511 448 10529|
3000 11.11149 537 500 10360
22516 6.6 899 512 7
14950 9.7 916 444 19 12913
4950 10.71054|517 19 12270
4950 12 1093 513 22 11842
14796
14950 15 1121 490 27 10656
8568 16.2|1066 464 39 11360
8568 17.6|1104 487 42 |11136
11220 15.8 1121 493 49 10814
4473 8.9 960 517 158 13523
3600 12.4 1079 515 311 |11289
3000 12.5|1041 490 400 11183
10400 15 1057 479 26 10951
6600 20 |1288 546 120 9722
5100 14.8 1288 590 204 10481
3600 15.5 1327 599 448 9812
3600 18.5|1371 626| 445 9669
3000 14.6|1327 599| 648 9643
3000 23.2 1427566 685 9115
3000 23.2 1427 621 685 9115
7280 14.3 1271 556 49 11588
7280 14.6 1271|556 88
10888
Transcribed Image Text:X1 X4 X2 X3 X5 Y 16630 15 1232 571 19 |11726 7900 15.6|1077 482 47 |11252 5100 10 963 485 123 12449 5160 12.3 1135 542 144 11030 3600 12.6 1113 534 295 10787 3000 12.3 1124 541 410 10603 3000 14.2 1204 553 515 10144 14000 15.9 1177 521 27 11674 3660 14.6|1135526 56 11510 5400 15.3 1149 514 172 10946 3600 14.2 1141 526 362 10508 3600| 11 |1149 544 354 10604 3600 14.2|1177 525 378 10270 3000 14.2|1116|511 448 10529| 3000 11.11149 537 500 10360 22516 6.6 899 512 7 14950 9.7 916 444 19 12913 4950 10.71054|517 19 12270 4950 12 1093 513 22 11842 14796 14950 15 1121 490 27 10656 8568 16.2|1066 464 39 11360 8568 17.6|1104 487 42 |11136 11220 15.8 1121 493 49 10814 4473 8.9 960 517 158 13523 3600 12.4 1079 515 311 |11289 3000 12.5|1041 490 400 11183 10400 15 1057 479 26 10951 6600 20 |1288 546 120 9722 5100 14.8 1288 590 204 10481 3600 15.5 1327 599 448 9812 3600 18.5|1371 626| 445 9669 3000 14.6|1327 599| 648 9643 3000 23.2 1427566 685 9115 3000 23.2 1427 621 685 9115 7280 14.3 1271 556 49 11588 7280 14.6 1271|556 88 10888
Use MS excel and the given data to estimate the least squares
multiple linear regression model defined by: E(y) = B0 + ß1x1 +
B2x2 + B3x3 + B4x4+ B5x5
Transcribed Image Text:Use MS excel and the given data to estimate the least squares multiple linear regression model defined by: E(y) = B0 + ß1x1 + B2x2 + B3x3 + B4x4+ B5x5
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