For a linear regression model, how do we interpret a Q-Q plot?

Data Science, AI and ML
#1

The Q-Q plot represents a graphical plotting of the quantiles of two distributions with respect to each other. In simple words, we plot quantiles against quantiles in the Q-Q plot which is used to check the normality of errors.

Whenever we interpret a Q-Q plot, we should concentrate on the ‘y = x’ line, which corresponds to a normal distribution. Sometimes, this line is also known as the 45-degree line in statistics.

It implies that each of the distributions has the same quantiles. In case you witness a deviation from this line, one of the distributions could be skewed when compared to the other i.e, normal distribution.