Class Notes - Simple linear regression From Wikipedia, the...

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Simple linear regression From Wikipedia, the free encyclopedia Jump to: navigation , search A simple linear regression is a linear regression in which there is only one covariate (predictor variable). Simple linear regression is used in situations to evaluate the linear relationship between two variables. One example could be the relationship between muscle strength and lean body mass. Another way to put it is that simple linear regression is used to develop an equation by which we can predict or estimate a dependent variable given an independent variable. The regression equation is given by Y = a + bX Where Y is the dependent variable, a is the y intercept, b is the gradient or slope of the line and X is independent variable. The linear relationship between the two variables (i.e. dependent and independent) can be measured using a correlation coefficient e.g. the Pearson product moment correlation coefficient . Arithmetic mean
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This note was uploaded on 08/15/2008 for the course BUSA 2182 taught by Professor Brown during the Spring '07 term at Savannah State.

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Class Notes - Simple linear regression From Wikipedia, the...

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