A linear pattern occurs on my residual plot: what can I do? I'm a bit stuck with a problem here and any kind of help would help a lot :)
Just to give a clue about my data. I have 6 independant variables (IV) which are:

*

*$X_1$ = Population -within a block-

*$X_2$ = Households -within a block-

*$X_3$ = Total Rooms -aggregated-

*$X_4$ = Total Bedrood -aggregated-

*$X_5$ = Median Income

*$X_6$ = Ocean Proximity [Categorical]

and my dependant variable (DV) is $Y$ = Median House Price.
I ran a regression including all IVs but there is a violation for almost all OLS assumptions in addition to huge multicollinearity. Here are the residual plot and normality plot before any adjustments.

What I did then is transform all my IVs and my DV using the Box-Tidwell method which I think it is not the correct way of solving the issue so this is my first question what can I do to solve the normality issue?
The other problem is that even after transforming all variables I still have an issue in my residual plot which is the main problem here. I have a linear pattern on the graph that I don't know how to solve. I run my DV against each IV separately and still have the same issue. Here is the graph for the transformed model.


Regarding the linear pattern: this happens frequently when your response takes the same value for a number of observations. For those observations, $(y-pred)$ is of course a linear function of $pred$, as $y$ is constant.
