Simple Linear Regression:
The simple linear regression is aimed at finding the "bestfit" values of two parameters  A and B in the following regression equation:

where Y_{i}, X_{i}, and E_{i} are the values of the dependent variable, of the independent variable, and of the random error, respectively. Parameter A is called "the slope of the regression line", B  "the yintercept of the regression line".
The initial data (sample) are N pairs (X_{i},Y_{i}). The regression equation describes a line in the XY plane, and the data are N points on that plane.
A popular method for finding the "bestfit" values of A and B (i.e. the slope and intercept of the line that best fits the data) is the Least Squares Method.
See also: Line of regression, Regression analysis
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