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The equation of the regression line is calculated so as to minimise the sum of the squares of the vertical distances between the observations and the line.
The regression line represents the relationship between the variables if (and only if) that relationship is linear. The equation of this line ensures that the overall discrepancy between the actual observations and the predictions from the regression are minimised and, in that respect, the line is the best that can be fitted to the data set. Other criteria for measuring the overall discrepancy will result in different lines of best fit.
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What is regression line?
Regression techniques are used to find the best relationship between two or more variables. Here, best is defined according to some statistical criteria. The regression line is the straight line or curve based on this relationship. The relationship need not be a straight line - it could be a curve. For example, the regression between many common variables in physics will follow the "inverse square law".
What is the process of finding line of best fit called?
Finding the line of best fit is called linear regression.
Given a linear regression equation of equals 20 - 1.5x where will the point 3 15.5 fall with respect to the regression line?
on the lineGiven a linear regression equation of = 20 - 1.5x, where will the point (3, 15) fall with respect to the regression line?Below the line
What is the relationship between correlation coefficient and linear regreassion?
A correlation coefficient is a value between -1 and 1 that shows how close of a good fit the regression line is. For example a regular line has a correlation coefficient of 1. A regression is a best fit and therefore has a correlation coefficient close to one. the closer to one the more accurate the line is to a non regression line.
What is the equation that shows the relationship among certain quantities?
The answer depends on the quantities and the nature of the relationship. It can be a line-of-best-fit (or regression line), or a formula.
