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The sales price (S) per square foot of a warehouse is strongly influenced by the truss height (fee), which from several warehouses and is provided below Truss Height 12 14 14 15 15 16 18-22 24-24 26 26 27 28 30 30 ines how high stored goods can be stacked. Truss heights and sales price per square foot were collected 35.53 37.82 36.90 40.00 38.00 37.50 41.05 48.50 47.50 46.20 50.35 49.13 48.07 0.90 S4.78 54.32 Price3 using your calculator and formulas provided in class. Round all answers to three decimal places he following expressions:
Predict the sales price for a specific warehouses having a truss height of 25 feet and do so in a way that conveys information about the precision of the prediction. (i.e. find a 95% prediction interval for the specific sales price per square foot). Write a statement of explanation. J.
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Regression Analysis: y(price) versus x(Truss) The regression equation is y.(price) = 23.2 + 1.01 x(Truss) PredictorCoef SE CoPredicted Values for New Observations New 95% CI o 210.880 (57.322, 61.099) (55.67, 62.744)x 95% PI (57-322, 61.099) (55.677, 62.744) X 2. 61 534 1.001(59.386, 63.682) (57.855, 65.213) X 0601 o.952 (58.ss8, 62.644) (56.982, 64.219) X 463 746 1.118 (61.347, 66.145) (59.915, 67.577)Xx 5. 61 712 1.011 (59.549, 63.885) (53.026, 65. 408) X 0.984 (59.098, 63.321) (57.552, 64. 867)X 7-64 812 1.175 (62.291, 67.333) (60.903, 68.720)xx 872 371 1.585 (68.971, 75.771) (67.846, 76.896) xx 1.530 (68.076, 74.637) (66.920, 75.793) xx 10 . 70 037 1.458 (66.911, 73.164) (65.713, 74.361)xx 11 74.248 1.688 (70.628, 77.868) (69.555, 78.941) Xx 12 13 010 1.620 (69.536, 76.485) (68-428, 77.592) Xx 13 71 935 1.561 (68.586, 75.283) (67.443, 76. 422)XX 1.718 (71.120, 78.492) (70.062, 79. 550)Xx 1578 743. 1.935 (74.593, 82.894) (73.630, 83. 857) Xx 16 22.-2 76 1.909 (74.181, 82.372) (73.208, 83.345)XX 14 .24..806 X denotes a point that is an outlier in the predictors XX denotes a point that is an extreme out lier in the predictors Values of Predictors for New Observations

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