4.1
Area Problem
A contractor needs to estimate the amount of paint required to cover a specific part of a wall with a curved top edge in one hundred model homes. To do this accurately, the wall’s surface area must be calculated.
If the curved edge follows a mathematical function, the problem reduces to finding the area under a given curve.
To approximate this area, the region beneath the curve is divided into n number of rectangles, of width Δx. The sum of the areas of these rectangles provides an estimate of the total area.
The height of each rectangle can be taken at the left endpoint or the right endpoint, which may lead to an overestimate or an underestimate depending on the curve’s shape.
A more balanced estimate uses the function’s value at any point inside each subinterval, called the sample point.
For each rectangle, the area is given by the function's value at the sample point multiplied by the width of the subinterval. Adding the areas of all the rectangles gives the approximate area.
As the number of rectangles increases and their width decreases, the sum approaches the integral, which provides the exact area under the curve. This helps estimate the exact amount of paint required.
Determining the area of a region with straight edges is straightforward, as geometric formulas for rectangles, triangles, and polygons can be applied directly. However, traditional geometric methods are insufficient when a region has a curved boundary, such as the area under a function.
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The area problem involves finding a systematic way to measure such regions. One approach to solving this problem is through approximation. Instead of attempting to compute the area exactly at the outset, the region under the curve is first divided into smaller, simpler shapes. A common method involves approximating the area using rectangles. By summing the areas of these rectangles, we obtain an estimate of the total area. The height of each rectangle is determined by evaluating the function at specific points along the interval. Different choices for these points may lead to overestimations or underestimations of the actual area.
As the number of rectangles increases and their widths become smaller, the approximation becomes more precise. In the limit, as the width of each rectangle approaches the minimum value, the sum of their areas converges to an exact value, which represents the true area under the curve. This process provides a rigorous foundation for defining areas in cases where curved boundaries are involved.
The method of approximating curved regions by breaking them into simpler geometric shapes extends beyond mathematics and is widely applied in physics, economics, and engineering. It allows for precise computations in scenarios involving accumulated quantities, such as work done by a varying force or total revenue over time.
A contractor needs to estimate the amount of paint required to cover a specific part of a wall with a curved top edge in one hundred model homes. To do this accurately, the wall’s surface area must be calculated.
If the curved edge follows a mathematical function, the problem reduces to finding the area under a given curve.
To approximate this area, the region beneath the curve is divided into n number of rectangles, of width Δx. The sum of the areas of these rectangles provides an estimate of the total area.
The height of each rectangle can be taken at the left endpoint or the right endpoint, which may lead to an overestimate or an underestimate depending on the curve’s shape.
A more balanced estimate uses the function’s value at any point inside each subinterval, called the sample point.
For each rectangle, the area is given by the function's value at the sample point multiplied by the width of the subinterval. Adding the areas of all the rectangles gives the approximate area.
As the number of rectangles increases and their width decreases, the sum approaches the integral, which provides the exact area under the curve. This helps estimate the exact amount of paint required.
From Chapter 4:
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