Really confusing table – what do coefficient, probability and R2 (adjusted) mean?
Regression analysis is investigation how one variable changes when another increases or decreases. The R-squared measures the proportion of the variation in the dependent variable that is explained by the behavior of the explanatory variables, it ranges from 0 to 1. E.g. 0.7 shows that 70% of the variation of dependent variable may be explained by variation of a chosen explanatory variable. When a number of explanatory variables is more than one, adjusted R-squared is rather used. The higher the adjusted R^2 value, the more accurately the explanatory (independent) variables included in the model will be able to explain the variation in the dependent variable; or vice versa, the model with a higher adjusted R^2 is able to estimate better the value of the dependent variable. R-squared is always smaller than R-squared and may be negative. Correlation coefficient permits to quantify the degree to which two variables tend to be related. That does not mean necessarily causal relationship, be
