Question

Application of the least squares method results in values of regression model parameters that minimize the sum of the squared deviations between the​

observed values of the independent variable and the predicted values of the dependent variable.

observed values of the dependent variable and the predicted values of the independent variable.

observed values of the independent variable and the predicted values of the independent variable.

observed values of the dependent variable and the predicted values of the dependent variable.

Answer 1

Solution :

Option D is correct.

Explanation :

"The line minimizes the sum of squared differences between observed values (the y values) and predicted values (the ŷ values computed from the regression equation)."

So, The least squares method is to find out the intercept and the slope of a regression line that minimizes the sum of the squared differences between: observed values of the dependent variable and predicted values of the dependent variable.

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