This question evaluates competency in critiquing observational study design and analysis, including recognition of sampling bias and external validity issues, regression model assumptions, confounding, diagnostic reasoning, and the distinction between descriptive and causal inference.
You have an observational, cross-sectional dataset of 1,000 adult Mountain View residents. The outcome is individual annual income (pre-tax). The exposure is a binary indicator of having completed a 4-year college degree (College = 1 if yes, 0 otherwise).
Is fitting a simple linear regression of income on a binary college indicator appropriate for this data? Discuss:
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