This will be the equation of the regression line. Substitute these values in the equation y = mx + b.So, if the slope is 3, then as X increases by 1, Y increases by 1 X 3 3. B the value of Y when X 0 (i.e., y-intercept). In the equation for a line, Y the vertical value. Determine the value of the y-intercept "b". Think back to algebra and the equation for a line: y mx + b. The steps to perform linear regression are given below: Here, m is the slope and b is the y-intercept. The equation of the linear regression line is of the form y = mx + b. Thus, a good model will be one that has the least residual or error. This implies that we are trying to reduce the difference between the observed response and the response that is predicted by the regression line. The main purpose of the least-squares method is to reduce the sum of the squares of the errors. Such a line is known as the regression line. We use the least-squares method to determine the equation of the best-fitted line for the given data points. How Does Linear Regression Calculator Work?
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