MATH 105 Lecture Notes - Lecture 22: Regression Analysis, Dependent And Independent Variables
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Definition: an approach in regression analysis to approximate the solution for a best-fit curve to a given set of points by minimizing the sum of the squares of the offsets. The sum of the squares of the offsets are used instead of the offset absolute values because this allows the residuals to be treated as a continuous differentiable quantity. A residual is the difference between an observed value of the response variable and the value predicted by the regression line. The sum of the residuals is always 0. The distance from the point to the line is the residual. The aim is to calculate the values m (slope) and b (y-intercept) in the equation of a line: y=mx+b. Hours of study vs. number of questions correct on exam: 81: for each (x,y) calculate x2 and xy: x. 15: sum x, y, x2 and xy (gives us x, y, x2 and xy): x.
