- Calculate the population increase: \(170.1 - 140 = 30.1 \text{ million}\).
- Express the increase in standard form to 1 significant figure: \(3 \times 10^7\).
- Calculate the area of Liberia: \(10 \times 1.1 \times 10^4 = 1.1 \times 10^5 \text{ km}^2\).
Final answers:
- Population increase: \(\boxed{30.1 \text{ million}}\)
- Standard form: \(\boxed{3 \times 10^7}\)
- Area of Liberia: \(\boxed{1.1 \times 10^5 \text{ km}^2}\)
Explanation
- Calculate population increase in Nigeria
To determine the population increase in Nigeria between 2007 and 2012, we subtract the initial population in 2007 from the final population in 2012.
Given:
Initial population (2007) = 140 million.
Final population (2012) = 170.1 million.
The increase is:
\[170.1 - 140 = 30.1 \text{ million}.\]
Thus, the increase in Nigeria's population during these 5 years was 30.1 million.
- Express increase in standard form to 1 significant figure
We need to express the increase of 30.1 million in standard form (scientific notation) to 1 significant figure.
First, convert 30.1 million into a standard numerical form:
\[30.1 \text{ million} = 30,100,000 = 3.01 \times 10^7.\]
Rounding \(3.01 \times 10^7\) to 1 significant figure gives:
\[3 \times 10^7.\]
Therefore, the increase expressed in standard form to 1 significant figure is \(3 \times 10^7\).
- Calculate the area of Liberia
We are given that the area of Liberia is approximately 10 times the area of The Gambia, and the area of The Gambia is \(1.1 \times 10^4 \text{ km}^2\).
The area of Liberia is:
\[10 \times (1.1 \times 10^4 \text{ km}^2).\]
Performing the multiplication:
\[1.1 \times 10 \times 10^4 = 11 \times 10^4 = 1.1 \times 10^5 \text{ km}^2.\]
The approximate area of Liberia is \(1.1 \times 10^5 \text{ km}^2\).
Examples
Understanding population growth and area calculations is vital for geography and urban planning. For instance, expressing large numbers in standard form (scientific notation) allows planners to handle data like national demographics or land measurements more easily. Similarly, scaling factors help experts estimate land use or resources required based on a known region's metrics relative to another. These mathematical skills are fundamental for interpreting statistical data in fields such as sociology, ecology, and logistics.