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Unformatted text preview: DSC 203 Quiz 4 I 20 points i 9/28/11 Name: k 6 3f ..__...__..__ A real estate agency collects data concerning y=sales price, x1=home size (in thousands of
dollars) and x2=rating [1 to 10, 1(worst) and 10(best)]. The agency wishes to develop a
regression model that can be used to predict the sales prices of future house it will list. Use the Minitab output below to answer the questions (2 points each). Predictor Coef SE Coef T P
Constant 29.347 4.891 6.00 0.001
Home_Size 5.6128 0.2285 24.56 0.000
Rating 3.8344 0.4332 8.85 0.000
s = R~Sq = 99.0% R—Sq(adj) = 98.7% Analysis of Variance Source DF SS MS F P
Regression 2 7374.0 3687.0 350.87 0.000
Residual Error 7 73.6 10.5 Total 9 7447.5 1. Write the estimated least squares regression equation. /é
\/ 7— ?iéiiﬁtr‘? t 51952'5?r‘<: “t” «3rgﬁt/l7zxap 2. Using a point estimate, predict the sales price of a house having 1800 square feet and a ratingon.
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3/ 2+ 26a 3%? F Sitoiwlif/if) i— aaawia) =2 @9593? if 0‘ MW} 3. Report the unexplained variation. What does this represent? (‘ﬂﬂ‘i Mimi):
“7 ﬁg d ﬁﬁarw n.1,»a‘ “a Writmg lei" ﬁgﬂ/Jfﬂég 35.725 grew
as 5. State the hypotheses to test the significance of the linear regression model. [110 5 ﬂ)! : p1 0 #5.; mt /€Q.;~:l*‘ are. ﬂag, ,2! a 6. State the p—value for the test in (5) and your conclusion. are—vacaer 31‘ ‘33 ﬂag} i _ . . The re. meme 6// Swag € {/6 ﬁéﬂ ce 433’ 3’5 (/éétjaicme of fine, More. as 03295“ “Er lgmjimmgl % i
7. interpret the coefficient for home size. i a?“
.. . Once Lou; mereeee 5} (were?) 3.. .t r. .. <. 3 AW.. ' f 5 g . feee mime” 1’” xi
“fl/iii: mini/153i Congr‘lﬁm—fa 8. State the p—value to determine the significance of the coefficient on home size. State the hypotheses. r H ﬂ 5 : f i {:3 3:. \ﬂﬂgj Thgrg 5e. GXf‘pgn/{ij ﬁffgoﬂﬁ Qr/(défﬂé’ “’féﬂﬁrf’ mﬂ’?§ gigsﬁ {c.33
liéﬁarﬁy r7175? 50.1.3352. rice. 9. Calculate a 90% confidence interval for the coefficient on ome size. log“: 9... ewe ‘94 s [Eerie Sb. == emit” all: ma— 5.2.1243:
Olef» 0‘9; 7" 5W 5.91253 232" ‘2 /‘ 3%,;
51a; 2g : r. 52%”; :> (ewes. were} 10. Use the output below to predict the mean sales price for a home that has 2000 square feet
and a rating of8. ' New Obs Fit SE Fit 95% CI 95% PI
1 11285.63 452.70 (10215.1?r 12356.09) (10215.15, 12356.12) / ’L $3,»? Wm WM be gigging/Ma md E/Qsﬂeme. ...
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 Fall '11
 Dr.Weese

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