Can someone break down the problem into 5 parts like shown below? I would greatly appreciate it!
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a signicant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x 772 628 518 508 496 483 |a (a) x = 502 feet (b) x = 646 feet lallEl--- (c) x=s1o feet (d>x=va1 feet Find the regression equation. mew (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Following is the scatter plot Stories, (y) 500 600 700 800 Height, (1) I y Iy 12 92 708 52 39936 539824 2704 628 48 30144 394334 2304 518 50 25900 268324 2500 511 27 13797 261121 729 491 38 18658 241081 1444 47s 34 16252 228484 1156 21:: EM: 21:9? ZI?= Ey?= 3394 249 144687 1983218 10837 Least Squares Regression Equation : y\" = 170 + 1211 Mung(2mm) nXIZ(zzr 6(144687) (3394)(249) 6(1983218) (3394)Q _ 868122845106 _ 23016 _ 11899308 - 11519236 _ 380072 Slope term, 171 : 0.0606 : 0.060557 a 0.0606 bo=g_b1i=&_b1& 71 11 24 4 = 719 (0.060557) L3: = 7.244954 m 7.2450 Intercept term, 170 : 7.2450 Least Squares Regrusion Eq\": ,0 7.2450 + (0.0606)x [E] at 1 = 502,y is estimated by: = 170 + hr '9 = (7.2450) + (0.0606)(502) m 37.644541 m 37.6445 1:502:13: E] at 1 : 652,y is estimated by: = be + 1711 g = (7.2450) + (0.0606)(652) = 46.728083 w 46.7281 1:652:13: In given sample data, 1 varied from 478 to 768, and given point 802 is outside the range of z;'s. Predicting in such a case is called extrapolation, and the results are unreliable as the regression model might not be valid outside the sample range. Not Meaningful But we can ignore this, and predict the equation nevertheless: at z = 802,y is estimated by: : 170 + 1711 (7.2450) + (0.0606)(802) m 55.811625 = 55.8116 9 Q E] at 1 : 736,37 is estimated by: Q = 170 + 1711 37 = (7.2450) + (0.0606)(736) m 51.814867 m 51.8149 z:736=@=
