Consider the data. xi 3 12 6 20 14 yi 65 35 50 15 20 The estimated regression equation for these data is Å· = 70 âˆ’ 3x. (a) Compute SSE,...

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Statistics

Consider the data.
x_i
3 12 6 20 14
y_i
65 35 50 15 20
The estimated regression equation for these data is
Å· = 70 âˆ’ 3x.
(a)
Compute SSE, SST, and SSR using equations
SSE = Î£(y_i âˆ’Å·_i)²,
SST = Î£(y_i âˆ’y)²,
and
SSR = Î£(Å·_i âˆ’y)².
SSE=SST=SSR=
(b)
Compute the coefficient of determination
r².
(Round your answer to three decimal places.)
r²
=
Comment on the goodness of fit. (For purposes of this exercise,consider a proportion large if it is at least 0.55.)
The least squares line did not provide a good fit as a smallproportion of the variability in y has been explained bythe least squares line.The least squares line provided a good fitas a small proportion of the variability in y has beenexplained by the least squares line.Â Â Â Â Theleast squares line did not provide a good fit as a large proportionof the variability in y has been explained by the leastsquares line.The least squares line provided a good fit as a largeproportion of the variability in y has been explained bythe least squares line.
(c)
Compute the sample correlation coefficient. (Round your answerto three decimal places.)

x_i	3	12	6	20	14
y_i	65	35	50	15	20

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The estimated regression equation for the above dataisHere n is the total number of observations and is the sample mean of the variable yais the sum of squares due to errorWe know thatFor See Answer

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