Linear Regression. Linear regression strives to show the relationship between two variables by applying a linear equation to observed data. The most common type of linear regression is a least squares fit which can fit both lines and polynomials among other linear models.
For more than one the process is called multiple linear regression. Linear regression is commonly used for predictive analysis and modeling. For example the weight of the person is linearly related to his height.
1 does a set of predictor variables do a good job in predicting an outcome dependent variable.
Multiple regression is a broader class of regressions that encompasses linear and nonlinear regressions with multiple. Linear regression strives to show the relationship between two variables by applying a linear equation to observed data. Linear regression calculator this simple linear regression calculator uses the least squares method to find the line of best fit for a set of paired data allowing you to estimate the value of a dependent variable y from a given independent variable x. For more than one the process is called multiple linear regression.
