So the regression line can be defined as Y = a +bX which is Y = 1.97 + 0.66 * Xġ.97 is the intercept which can be defined as the value which remains constant irrespective of the changes in the independent variable.Ġ.66 in the equation is the slope of the linear regression, which defines how much of the variable is the dependent variable on the independent variable. Now, first, calculate the intercept and slope for the regression equation. We have all the values in the above table with n = 4. You need to calculate the linear regression line of the data set.įirst, calculate the square of x and product of x and y 0.95 in the equation is the slope of the linear regression, which defines how much of the variable is the dependent variable on the independent variable.1.5 is the intercept which can be defined as the value which remains constant irrespective of the changes in the independent variable.x here is an independent variable, and y is the dependent variable which changes with the change in the value of x by a certain value.So the regression line can be defined as Y = a +bX which is Y = 1.5 + 0.95 * X
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