It gives values of coefficients that can be used to build the model for future predictions. The other important part of the entire output is a table of coefficients. Or in another language, information about the Y variable is explained 95.47% by the X variable. In this case, the R Square value is 0.9547, which interprets that the model has a 95.47% accuracy (good fit). One important part of this entire output is R Square/ Adjusted R Square under the SUMMARY OUTPUT table, which provides information, how good our model is fit. However, interpreting this output and make valuable insights from it is a tricky task. Till here, it was easy and not that logical.
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