I'm trying to understand the coefficient of determination and I want to know which interpretation of it is the most accurate or best represents its meaning.
7 answers
Silvia
Mon Oct 14 2024
R² lies within the range of 0 to 1, with each value carrying a specific significance in terms of model performance.
CryptoAlchemy
Mon Oct 14 2024
When R² equals 0, it indicates that the model fails to explain any variation in the dependent variable, essentially meaning the model has no predictive value.
Martino
Mon Oct 14 2024
Conversely, an R² value of 1 signifies that the model perfectly predicts the outcome, capturing all variations in the dependent variable.
mia_rose_painter
Mon Oct 14 2024
The closer R² is to 1, the stronger the model's ability to predict the dependent variable, implying a higher degree of accuracy and reliability.
Federico
Mon Oct 14 2024
The coefficient of determination, commonly denoted as R², is a vital statistical metric used to evaluate the predictive power of a model.