# HW13 - 11.2(a Z 3 x 707 E y m 553 Z 52 x 57,557 235.5 5...

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Unformatted text preview: 11.2 (a) Z. 3:,- x 707, E. y,- m 553, Z) 52;? x 57,557, 235.5. 5 53,258,111 5 9. # (9}(53, 258) — (707M658) a, b “ W " “7“! = 555 — {0.7771){707) :12. 2. g [353 [1 11.5 (a) Z 1“,; = 675, Z yz- = 433, 211:? : 37, 125, 23:4}, = 25, [105, ’n = 18. Therefore, _ (15)(25, 505) — (575){435) _ b "" {15)(37,125) — (575,12 "" Q5676” = 455 — (U.56?6)(675) =". 24. 18 585 EL Hence 3'} = 5.3254 + 0.55763 [13) The scatter plot and the regression line are shown below. Grams 3|] 4|] 5|] 2|] In Me Temperature 0, 3} : 5.8254 + (U.5676)(5U) = 34.205 grams. yr-\ 33: lg a 5-} If :3 11.10 (a) 2 = ed”, 1112 = lnc+ (1nd]1u; setting 31 = lnz, a = 1111:, b = 1nd, and 3} = a + bar, we have 23:11: 1 2 2 3 5 5 3121112. 8.7562 8.6473 8.6570 8.5932 8.5142 8.4960 2 331; 3 18, : y»; = 51.6639, 2 IL"? 3 68, Z: Egyi: 154.11.954.11. 3 6. 1' _ _ (6)(154.1954) — (18)(51.6639) _ _ E1 -1113 _ W _ 6.6669, 2 51.6639 — (—ﬂ.0569)(18) 2. 1. 6 8783 e=lnc Now a = ems = 66113364, 6! = 4-010569 = 0.9447, and 3 = 66113364 x 0.9447‘“. (b) For 1.1: e 4, .3 2 66113364 x 0.94474 = \$6166.16. 11.15 The least squares estimator A of or is a linear combination of normallyr distributed random variables and is thus normal as well. em) = so? — .36) = 13(17)— :EE{B) = 4 + 63 — 66 = .4, 2 -22 a 2217 2m 2 m 2 -2 2 _ _ .... - _ .... 0A —UP_Bi—J}7+£ 0'3 — ELEUYB— E+n—I smce aYB—ﬂ. (174-53)2 i=1 Hence n 2 2554: 2 i=1 2 ...
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