Statistics and Data Science Education / Scatterplot Regression Defense
Focus attention on the fragile lines first, then carry the same logic into later checkpoints.
Checkpoint 2
Hotspot Questions
This step narrows attention to the few lines that control the modeling workflow. Students are not yet tracing execution; they are proving they know what each critical line is for.
R 4.3 | Focus: Data Science & Statistics | Hotspot, Trace, Mutation, Repair
Learning goal
Inspect the most fragile logic lines first, then carry the same reasoning model into the trace stage.
Responses entered here become evidence for the later prediction and repair checkpoints.
source_submission.py
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Operational Intent
Why is lm(exam_score ~ hours_studied, ...) the line that anchors the statistical claim?
Boundary Logic
What role does geom_smooth(method = "lm") play in the scatterplot?
Edge Case Analysis
Why does this workflow remove incomplete rows before fitting the model or drawing the plot?
If the explanation is solid here, the next step asks for mental execution of the same logic without running the code.
Responses save automatically
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