Figure 1: The results of multiple linear regression depend on the correlation of the predictors, as measured here by the Pearson correlation coefficient r (ref. 2). (a) ...

Correlation coefficients are used to measure the strength of the linear relationship between two variables.; A correlation coefficient greater than zero indicates a positive relationship, while a ...

The major outputs you need to be concerned about for simple linear regression are the R-squared, the intercept (constant) and the GDP's beta (b) coefficient. The R-squared number in this example ...

A correlation of 0.0 shows no linear relationship between the movement of the two variables. ... You can think of regression to the mean and correlation as the flip sides of the same coin.

A Refresher on Regression Analysis. Understanding one of the most important types of data analysis. by Amy Gallo. November 4, 2015. uptonpark/iStock/Getty Images. Leer en español Ler em português.