In regression analysis, the existence of a high degree of inter-correlation among some or all of the explanatory variables in the regression equation constitutes

autocorrelation.

nonlinearities.

heteroscedasticity.

multicollinearity.

(select one)

When using a multiplicative power function (Y = a X1b1 X2b2 X3b3) to represent an economic relationship, estimates of the parameters (a, b's) using linear regression analysis can be obtained by first applying a ____ transformation to convert the function to a linear relationship.

semilogarithmic (using a logarithmic transformation on one side of the equation only)

double-logarithmic (using a logarithmic transformation on both sides of the equation)

reciprocal

polynomial

(select one)

autocorrelation.

nonlinearities.

heteroscedasticity.

multicollinearity.

(select one)

When using a multiplicative power function (Y = a X1b1 X2b2 X3b3) to represent an economic relationship, estimates of the parameters (a, b's) using linear regression analysis can be obtained by first applying a ____ transformation to convert the function to a linear relationship.

semilogarithmic (using a logarithmic transformation on one side of the equation only)

double-logarithmic (using a logarithmic transformation on both sides of the equation)

reciprocal

polynomial

(select one)

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In regression analysis, the existence of a high degree of inter-correlation

among some or all of the explanatory variables in the regression equation

constitutes

autocorrelation....