The fit function of type y = a + bx for the following points using the least square method.

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Suresh Chand · Accepted Answer

Solution: X Y XY X2 -1 1 -1 1 1.2 20 24 1.44 2 27 54 4 2.7 33 89.1 7.29 3.6 41 147.6 12.96 4 45 180 16 Σx = 125 Σy = 167 Σxy = 493.7 Σx2 =42.69 n = 6 Here, the regression formula is y = a + bx -------- (i) The regression cofficient can be found as b = (frac{nΣxy - ΣxΣy}{nΣx^2 - (Σx)^2}) =(frac{6 times 493.7 - 12.5 times 167}{6 times 42.69 - 12.5^2}) = 8.756 Now, (a = bar{y} - b bar{x}) = (frac{Σy}{n} - bfrac{Σx}{n}) = (frac{167}{6} - 8.756 times frac{12.5}{6}) = 9.592 Therefore, the fitted regression function is ŷ = 9.592 + 8.756 x

The fit function of type y = a + bx for the following points using the least square method.

X -1 1.2 2 2.7 3.6 4

F(x) 1 20 27 33 41 45

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The fit function of type y = a + bx for the following points using the least square method. X -1 1.2 2 2.7 3.6 4 F(x) 1 20 27 33 41 45

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The fit function of type y = a + bx for the following points using the least square method.

X -1 1.2 2 2.7 3.6 4

F(x) 1 20 27 33 41 45