# The co-efficient of determination or r-squared R-squared is a statistical measure of how close the data is to the fitted regression line. R-squared is always between 0 and 100%. The higher the R-squared, the better the model fits your data. ## The R-squared coefficient The R-squared coefficient, also known as the coefficient of determination, is a measure of how well a model fits a dataset. It is commonly used in statistics. It measures the degree of variation in the target variable; this is explained by the variation in the input features. An R-squared coefficient generally takes a value between 0 and 1, where 1 equates to a perfect fit of the model. how do I know how good my regression is? How well does my line fit my data? That's where r-squared comes in, and r-squared is also known as the coefficient of determination. Again, someone trying to sound smart might call it that, but usually it's called r-squared. **It is the fraction of the total variation in Y that is captured by your models.** So how well does your line follow that variation that's happening? Are we getting an equal amount of variance on either side of your line or not? That's what r-squared is measuring.