A statistical technique used to explain or predict the behavior of a dependent...

The equation of the regression function. It may be of any functional form and the terms may be orthogonal or not.

Description of the “best fit” summary of the relationship between pairs (or more complex sets) or data. Like the mean, the regression line does not describe actual data (except in trivial cases); the regression equation is convenient summary. It is constructed as the line that minimizes the sum of differences between each point and the regression line in a scattergram. In the most common, straight line or linear case, the point estimate of the mean is replaces by a “running” point with the formula y = c + b * x, where y is the dependent or predicted value in each pair of observations and x is the independent or predictor value in each pair. C in this equation is called the intercept and a is the slope of the regression line. [See intercept, prediction, residual, slope, standard error

rising bottoms RSI