I have a dataset having 252 observations. There are two variables having a defined and known linear relationship. By computation, I found 4 observations do not follow the linear equation, and I conclude the difference is due to data entry errors.
Although those two variables are not used in my regression model, I am still concerned the reliability of those 4 observations.
My question is should I remove those 4 observations from the dataset, before doing a linear regression?
There are two variables "body fat" and "density". The value of "body fat" is computed by "density" using a linear formula, stated by the creators of this dataset. I found those 4 entries are far off from the given formula, whereas all others are exactly follow the formula.