Assumptions are needed to draw accurate conclusions about reality test Different assumptions are made for various statistical models and in order for models to reflect reality accurately; their assumptions need to be true. If assumptions are broken, accurate conclusions cannot be drawn about the data distribution. Therefore, part of the data process involves checking to make sure that your data doesn't fail this assumption.