Approximating Areas under Curves

In summary, The formula for a regular partition in this textbook is x_k=a+k\Delta x, \text for k=0,1,2,...,n. To find "k", one can use the formula $\Delta x = \frac{b-a}{n}$ where $[a,b]$ is the interval and n is the number of times it is divided. The points in the partition will then be $a, a+\Delta x, a+2\Delta x,\ldots, a+(n-1)\Delta x, b$. The interval can be divided into equal parts or any desired number of parts.
  • #1
alane1994
36
0
I am learning this right now, and I am having troubles with something.
For regular partition, the formula in my textbook is this.

[tex]x_k=a+k\Delta x, \text for k=0,1,2,...,n.[/tex]

My question is this, how does one find "k"? It is very important clearly!;)
 
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  • #2
alane1994 said:
I am learning this right now, and I am having troubles with something.
For regular partition, the formula in my textbook is this.

[tex]x_k=a+k\Delta x, \text for k=0,1,2,...,n.[/tex]

My question is this, how does one find "k"? It is very important clearly!;)

$\Delta x = \frac{b-a}{n}$ where $[a,b]$ and n is the number of times you want to divide the interval.

The points in the partition will then be $a, a+\Delta x, a+2\Delta x,\ldots, a+(n-1)\Delta x, b$

Usually you are told how many times to divide the interval.
 
  • #3
Or perhaps you decide, rather than being told. A partition doesn't have to necessarily be divided in parts of equal length, but it's certainly easier. :D
 

Related to Approximating Areas under Curves

1. What is the purpose of approximating areas under curves?

Approximating areas under curves is used to estimate the total area under a curve on a graph. This can be useful in many scientific fields, such as physics, biology, and economics, as it allows us to make predictions and understand the behavior of a system.

2. How is the area under a curve approximated?

The area under a curve can be approximated by dividing it into smaller, simpler shapes, such as rectangles or trapezoids, and then calculating the sum of their individual areas. This is known as numerical integration and can be done using various methods, such as the Trapezoidal Rule or Simpson's Rule.

3. What factors can affect the accuracy of the approximation?

The accuracy of the approximation can be affected by the number of smaller shapes used, the size of each shape, and the complexity of the curve. Generally, the more smaller shapes used, the more accurate the approximation will be. However, using too many shapes can also lead to errors due to rounding and truncation.

4. How does the shape of the curve impact the accuracy of the approximation?

The shape of the curve can greatly impact the accuracy of the approximation. If the curve is smooth and doesn't have any sharp turns or irregularities, then the approximation will be more accurate. However, if the curve has sharp turns or spikes, the approximation may be less accurate and may require more smaller shapes to get a more precise estimation.

5. In what real-world situations is approximating areas under curves used?

Approximating areas under curves is used in many real-world situations, such as calculating the volume of a liquid in a container, predicting population growth, and estimating the total cost of a project. It is also commonly used in physics to calculate the work done by a variable force or the displacement of an object over time.

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