Answer :
To determine the addition of an independent variable to the model makes the linear regression model better the following technique is used.
In general, and without a doubt, you are referring to a novel and distinct variable that may also have a strong link with some other factors. See, if it has a low correlation, it will unquestionably add a considerable amount of accuracy to the model [accuracy in the sense of correctness; you can also compare before and after adding the variable using any metric, such as R-square or any other coefficient of determination]. Whatever the new variable is, it will undoubtedly add to our understanding of the data, making the regression line's fit to the data more accurate. We typically ignore it if it has a high degree of resemblance to another variable and doesn't add any new information to the data, however if there is hardly any similarity between it and what we can, and even this makes the model less accurate.
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