Inferring interesting conclusions about real statistical populations almost always requires some background assumptions.
In the design-based approach, the model is taken to be known, and one of the goals is to ensure that the sample data are selected randomly enough for inference.
Scenario: Imagine a study assessing the effectiveness of a new teaching method in multiple classrooms.
Students within the same classroom may share common characteristics or experiences, leading to correlated observations.
Consequence: Failure to account for this lack of independence may inflate the perceived impact of the teaching method, as the outcomes within a classroom may be more similar than assumed.