Find the linear regression equation using the database below. In this case, we wish to use the equation to predict y given x. X Y x y 2 45 92 1967 2 45 100 2138 3 67 101 2159 6 131 103 2202 7 152 112 2394 18 387 124 2651 19 408 124 2651 25 537 125 2672 26 558 126 2693 33 707 133 2843 36 771 37 793 40 857 43 921 51 1092 57 1220 64 1369 69 1476 71 1519 83 1775 Solution The output from my regression: ------------------------------------------------------------ ------------------ y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+--------------------------- ------------------------------------- x | 21.36778 .0060731 3518.42 0.000 21.35377 21.38178 _cons | 1.073333 .6971131 1.54 0.162 -.5342123 2.680879 ------------------------------------------------------ ------------------------ In other words, the prediction line is: y = 1.073333 + 21.36778 * x..

1. Find the linear regression equation using the database below. In this case, we wish to use the
equation to predict y given x.
X Y x y
2 45 92 1967
2 45 100 2138
3 67 101 2159
6 131 103 2202
7 152 112 2394
18 387 124 2651
19 408 124 2651
25 537 125 2672
26 558 126 2693
33 707 133 2843
36 771
37 793
40 857
43 921
51 1092
57 1220
64 1369
69 1476
71 1519
83 1775
Solution
The output from my regression: ------------------------------------------------------------
------------------ y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------
------------------------------------- x | 21.36778 .0060731 3518.42 0.000 21.35377 21.38178 _cons |
1.073333 .6971131 1.54 0.162 -.5342123 2.680879 ------------------------------------------------------
------------------------ In other words, the prediction line is: y = 1.073333 + 21.36778 * x.