3 ms·

Adjusted R^2 of 0.14. Call me a cynic

• deleted 3y ago
  [deleted]
• vouaobrasil 3y ago
  The adjusted R^2 is not what indicates the quality of a result, but rather the p-value...R^2 indicates an effect size, whereas p-value indicates significance. A small R^2 just means there are other things that should be in the model.
  • safgasCVS 3y ago
    - P-value is the result of a hypothesis test with the question being "is this effect size 0". The p-value is the probability of seeing the observed data under the assumption of the effect being zero. - The R^2 is a measure of how well the regression model 'explains' the observed data so to speak. - The effect size is contained in the coefficients assuming near perfect independence between the variables