Prediction of body weight from testicular and morphological characteristics in indigenous Mengali sheep of Pakistan: Using factor analysis scores in multiple
linear regression analysis.
Association between estimated and observed body weight using simple
linear regression model.
The data for standard multivariate regression are summarized in Table 2, whereas the data for robust
linear regression are included in Table 6 of the online Data Supplement.
Compare the multiple
linear regression recognition system with the traditional minimum distance method [11] with the same training data.
On the other hand, simple
linear regression finds the best line that predicts one variable from another.
The estimate of the ideal dose of the regulator through plant lodging indicated
linear regression equations, regardless of the doses of N-fertilizer (Table 2).
Looking for multiple
linear regression function, the hypothesis on regression linear dependence is verified.
Therefore, 10 nearest-neighbor samples were included in the fuzzy
linear regression prediction model in each subset.
The simple
linear regression model between sucrose content (Suc) and the apparent purity (Ap), polarization (Pol) and brix (Bx) is as follows:
In case of positive correlation, each two parameters have been studied in simple
linear regression. Then, these parameters prediction equations were established.
In this paper we use
linear regression analysis to show two paradoxes in regression analysis.