(a) Compute the coefficient of determination, R? R?. % (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in is explained by the least-squares regression model. According to the residual plot, the linear model appears to be (Round to one decimal place as needed.)
Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The
correlation coefficient is 0.944 and the least squares regression line is y = 0.199x + 11.982. Complete parts (a) and (b)
below.
Height, x
27.5 25.5 26.25 25.25 27.5 26.25 26 27.25 27.25 27 27.25 Ф
Head Circumference, # 17.5 17.0 17.2 17.0 17.5 17.3 17.2 17.4 17.3 17.3 17.4
(a) Compute the coefficient of determination, R?
R?.
% (Round to one decimal place as needed.)
(b) Interpret the coefficient of determination and comment on the adequacy of the linear model.
Approximately % of the variation in
is explained by the least-squares regression model.
According to the residual plot, the linear model appears to be (Round to one decimal place as needed.)
Given that,
Dependent variable (y) = head circumference
Independent variable (x) = height
Sample size (n) = 11
Correlation coefficient (r) = 0.944
The regression equation is,
y = 0.199x + 11.982
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