Data Collectionmedium
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A survey on income and employment includes automatic validation rules: Age must be 18–75; Annual household income must be $0–$500,000; Years of education must be 0–20. Of 1,000 responses, 23 age entries violate these rules (e.g., age = 156) and 18 income entries violate them (e.g., income = $2,500,000). A data manager manually reviews original survey forms and corrects 21 age errors and 15 income errors. However, 3 age entries and 3 income entries cannot be verified from the original forms. Which is the best approach for handling the 6 unverifiable entries?
A survey on income and employment includes automatic validation rules: Age must be 18–75; Annual household income must be $0–$500,000; Years of education must be 0–20. Of 1,000 responses, 23 age entries violate these rules (e.g., age = 156) and 18 income entries violate them (e.g., income = $2,500,000). A data manager manually reviews original survey forms and corrects 21 age errors and 15 income errors. However, 3 age entries and 3 income entries cannot be verified from the original forms. Which is the best approach for handling the 6 unverifiable entries?