HW 6 excel

HW 6 excel - the regression line is a good fit for the...

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X Y Projected Y Residual 22.06 34.38 31.129998 -3.250002 19.88 30.38 29.771204 -0.608796 18.83 26.13 29.116739 2.986739 22.09 31.85 31.148697 -0.701303 17.19 26.77 28.094527 1.324527 20.72 29 30.294776 1.294776 18.1 28.92 28.66173 -0.25827 18.01 26.3 28.605633 2.305633 18.69 29.49 29.029477 -0.460523 18.05 31.36 28.630565 -2.729435 17.75 27.07 28.443575 1.373575 19.96 31.17 29.821068 -1.348932 17.87 27.74 28.518371 0.778371 20.2 30.01 29.97066 -0.03934 20.65 29.61 30.251145 0.641145 20.32 31.78 30.045456 -1.734544 21.37 32.93 30.699921 -2.230079 17.31 30.29 28.169323 -2.120677 23.5 28.57 32.02755 3.45755 22.02 29.8 31.105066 1.305066 The data is linear but it has a very weak correlation. The direction is positive and fairly random. 52.3 percent of the variability in Y is explained by X. The data is correlated a bit but the strength of the relationship is somewhat weak. The residual plot is very random which shows that
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Unformatted text preview: the regression line is a good fit for the data, even with the weak correlation. RESIDUAL OUTPUT ObservationPredicted YResiduals 1 31.13077 3.249233 2 29.77193 0.608067 3 29.11745 -2.987448 4 31.14947 0.700533 5 28.09521 -1.325206 6 30.29552-1.29552 7 28.66243 0.257574 8 28.60633 -2.306327 9 29.03018 0.459816 10 28.63126 2.72874 11 28.44426 -1.374264 12 29.8218 1.348202 13 28.51906 -0.779062 14 29.97139 0.038605 15 30.25189 -0.641888 16 30.04619 1.733807 17 30.70068 2.229323 18 28.17 2.119996 19 32.02835 -3.458346 20 31.10583 -1.305834 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 f(x) = 0.6233185448x + 17.380360088 R = 0.2736575708 15 16 17 18 19 20 21 22 23 24-5 5 Residual Plot X Variable 1 Residuals...
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