What are the relation and differences between time series and linear regression?
I have a strong grasp of linear regression, and a beginner's grasp on time series analysis; I know the Box-Jenkins method and understand the concepts. To solidify this understanding, I would like to compare and contrast the two methods to understand if time series analysis is an extension of linear regression.
Maybe the best way to answer this question is to compare and contrast the model assumptions of each method. Does time series analysis share all assumptions of linear regression, with a few extra assumptions added in (related to autocorrelation, stationarity, etc.)?
Note: This question has been asked here but the answers go off-topic and discuss the flaws of a Cornell professor's understanding of time series analysis. I do not have enough reputation to comment on that thread.