3. A college student is accessing a large database that contains literacy rates and geographical locations classified as urban or rural. The student is only interested in literacy rates of urban areas. Which action should the student use to narrow the data scope?
Answer: D
Filtering out rural areas will effectively narrow the data scope to only urban literacy rates.
By filtering out rural areas, the student will be left with data that exclusively pertains to urban literacy rates, which aligns perfectly with their research interest.
A) Filter out area urban
This option would incorrectly remove urban areas from the dataset, leaving the student with rural data. Since the student is specifically interested in urban literacy rates, this action would not serve their purpose.
B) Sort by area, urban and rural
Sorting the data does not eliminate any information; it merely organizes it. Therefore, while the student would be able to see urban and rural data separately, they would still have access to both datasets, which does not fulfill their need to focus solely on urban areas.
C) Sort by literacy rate
Sorting by literacy rate would arrange the data based on the rates themselves, but it would not filter out the rural data. The student would still see both urban and rural literacy rates, which is not what they are specifically looking for.
D) Filter out area, rural
By filtering out rural areas, the student successfully narrows the dataset to include only urban areas. This directly addresses their interest in urban literacy rates and allows for a more focused analysis of the relevant data.
Conclusion
Filtering out rural areas is the most effective way for the student to narrow their data scope to urban literacy rates. The other options either fail to eliminate the unwanted rural data or do not provide a focused view of the urban literacy rates needed for their research. Thus, option D is definitively the correct choice.