ECOR 1010 Chapter Notes - Chapter 20: Cartesian Coordinate System, Scatter Plot, Standard Deviation

• School: Carleton University
• Department: Engineering Common Core Courses
• Course: ECOR 1010
• Professor: Henry Saari

Document Summary

Linear least square regression: permits calculation of the coefficients of the line that fits the data such that the sum of the squares of the error is the least. Linear correlation analysis: descriptive measure of the degree to which two things change relative to each other linearly. The slope of the line relating two variables is the constant of proportionality. Each observation is represented as a point in an orthogonal cartesian coordinate system. These pairs of coordinates can be described abstractly in terms of their position relative to the x and y axes. If the regression line in a scatter plot is horizontal, it is safe to conclude that there is no relationship between both variables. The desired constraint on the line is that the errors as a whole be minimized. This difference is called the error of the estimate, or residual e= y y.