Do my results suggest the assumption of homoscedasticity was violated? I ran a multiple regression with 16 predictors and did assumption testings. I am not sure if my graph shows homoscedasticity, I googled and the information that I have gathered suggests that my data is neither funnel-shaped nor randomly scattered.


When we build a linear regression, we try to estimate the accuracy of a chosen model. For this purpose we use LM, RESET and others tests. Also, there is a famous “residual - fitted values” plot we use for testing the correctness of our model.
In a good model (for the first look), covariance between fitted values (of dependent variable) and studentised (or standardised) residuals must be zero (except one case known for me). So, you could see that you have the wrong functional form of your model, this exactly we could see on your graph. You should try to build another type of regression model and do not look at the other assumptions of Classical linear model in this regression with the wrong functional form.
