I have done regression on a dataset and observed that-
1. Data has homoscedasticity - in scale vs location plotline is approx. horizontal. And residuals are evenly spread out along both sides of the line.
2. R-squared value is less than 8%
How do I interpret this?
Shantanu Kumar Rahut
A low R-squared value shows that your independent variable is not trying to describe much of the alteration in your dependent variable - regardless of variable significance, this is letting you know that the identified independent variable, while significant, is not accounting for much of your data's mean.
This pairing indicates that the independent variables are correlated with the dependent variable, but that they do not explain a large portion of the variability in the dependent variable.
R-squared doesn't somehow indicate whether a regression model fits your data well. The R2 value of a good model can be low. A biased model, on the other hand, can have a high R2 value!
Dear Dr Shantanu Kumar Rahut . This combination indicates that the independent variables are correlated with the dependent variable, but they do not explain much of the variability in the dependent variable.See the link: https://statisticsbyjim.com/regression/low-r-squared-regression/
Kindly see also the following use link: https://statisticsbyjim.com/regression/interpret-r-squared-regression/
- Badges
- Science topic
- Similar topics
- Mathematics
- Statistics
- Regression