<human>:  Can you tell me how to interpret a regression analysis?
<bot>: Start by understanding what regression analysis is. It is a statistical process used to identify the strength of the relationship between one dependent variable (usually denoted by Y) and a series of other changing variables (known as independent variables and denoted by X). 2 Next, look at the regression analysis results. The results from a simplest linear regression output might include the following information: the intercept, the slope of the regression line, the coefficient of determination (R-squared) and other statistics that indicate the overall fitness of the model to your data. 3 Now, begin to interpret the results of the regression analysis. The intercept represents the estimated mean value of the dependent variable when all independent variables are equal to zero. The slope of the regression line indicates the estimated change in the dependent variable according to a unit change in the independent variables. 4 Finally, look at the coefficient of determination. This is an indication of what portion of the total variation of the dependent variable is explained by the regression model. The closer the value is to 1, the better the model is at predicting values of the dependent variable based on the independent variables.