Which method below could provide an estimate for the number of mailboxes in a neighborhood? A: N = (number of mailboxes on one street) × (number of streets in the neighborhood) B: N = (number of mailboxes on one street) ÷ (number of streets in the neighborhood) C: N = (number of mailboxes in the neighborhood) ÷ (number of streets in the neighborhood) D: N = (number of mailboxes in the neighborhood) × (number of streets in the neighborhood)

The correct method to estimate the number of mailboxes in a neighborhood is A: N = (number of mailboxes on one street) × (number of streets in the neighborhood).

This method assumes that each street has approximately the same number of mailboxes and, by multiplying that number by the total number of streets, gives an overall estimate of the total number of mailboxes in the neighborhood.

To further explain, this type of estimation problem involves making assumptions based on averages or typical cases. In this scenario, we assume that the number of mailboxes on one street represents an average street in the neighborhood.

• Method B suggests dividing, which would likely give you the average number of mailboxes per street, which is not what we are looking for.
• Method C is incorrect because if you already knew the total number of mailboxes in the neighborhood, you wouldn't need an estimate. Additionally, dividing this number by the number of streets would give you an average number of mailboxes per street (similar to B).
• Method D is simply the opposite of what you want; it would only be used if you were trying to exaggerate the number dramatically, as this would multiply the total number of mailboxes by the number of streets, resulting in an impossibly large number.

Thus, Method A is the most sensible approach for estimation because it uses multiplication to approximate the total based on observable data from a representative sample (one street). This type of estimation is used in various fields like demographics studying, urban planning, and even marketing to make projections and decisions based on limited data.