Justine's question at Yahoo Answers regarding the Midpoint and Trapezoidal Rules

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In summary, the midpoint and trapezoidal rules can be combined to show that (1/2)(T_n+M_n)=T_{2n}. This relationship helps us to approximate integrals with even greater accuracy.
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MarkFL
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Here is the question:

Trapezoidal and Midpoint Estimates?


Show that (1/2)(Tn+Mn)=T2n

I have posted a link there to this topic so the OP can see my work.
 
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  • #2
Hello Justine,

First, let's look at the definitions of the two rules:

Midpoint Rule:

The Midpoint Rule is the approximation \(\displaystyle \int_a^b f(x)\,dx\approx M_n\), where

\(\displaystyle M_n=\frac{b-a}{n}\left[f\left(\frac{x_0+x_1}{2} \right)+f\left(\frac{x_1+x_2}{2} \right)+\cdots+f\left(\frac{x_{n-1}+x_{n}}{2} \right) \right]\)

Trapezoidal Rule:

The Trapezoidal Rule is the approximation \(\displaystyle \int_a^b f(x)\,dx\approx T_n\), where

\(\displaystyle T_n=\frac{b-a}{2n}\left[f\left(x_0 \right)+2f\left(x_1 \right)+\cdots+2f\left(x_{n-1} \right)+f\left(x_{n} \right) \right]\)

We can divide the interval $[a,b]$ into $2n$ equally spaced partitions, as so we may then write:

\(\displaystyle M_n=\frac{b-a}{n}\left[f\left(\frac{x_0+x_2}{2} \right)+f\left(\frac{x_2+x_4}{2} \right)+\cdots+f\left(\frac{x_{2n-2}+x_{2n}}{2} \right) \right]\)

And so using the midpoint formula, this becomes:

\(\displaystyle M_n=\frac{b-a}{2n}\left[2f\left(x_1 \right)+2f\left(x_3 \right)+\cdots+2f\left(x_{2n-1} \right) \right]\)

Likewise, the Trapezoidal Rule may now be written:

\(\displaystyle T_n=\frac{b-a}{2n}\left[f\left(x_0 \right)+2f\left(x_2 \right)+\cdots+2f\left(x_{2n-2} \right)+f\left(x_{2n} \right) \right]\)

Multiplying both by \(\displaystyle \frac{1}{2}\) and adding, we find:

\(\displaystyle \frac{1}{2}\left(T_n+M_n \right)=\frac{b-a}{2(2n)}\left[f\left(x_0 \right)+2f\left(x_1 \right)+\cdots+2f\left(x_{2n-1} \right)+f\left(x_{2n} \right) \right]\)

And using the definition of the Trapezoidal Rule, we find:

\(\displaystyle \frac{1}{2}\left(T_n+M_n \right)=T_{2n}\)
 

Related to Justine's question at Yahoo Answers regarding the Midpoint and Trapezoidal Rules

1. What are the Midpoint and Trapezoidal Rules?

The Midpoint and Trapezoidal Rules are numerical integration methods used in calculus to approximate the area under a curve. They involve dividing the curve into smaller sections and using the formula for the area of a rectangle or trapezoid to calculate the approximate area under the curve.

2. When should I use the Midpoint Rule and when should I use the Trapezoidal Rule?

The Midpoint Rule is more accurate for functions that are smooth and concave up, while the Trapezoidal Rule is better for functions that are less regular and have more variation. Generally, the Midpoint Rule is preferred for its higher accuracy, but the Trapezoidal Rule may be easier to use for certain functions.

3. How do I calculate the error in the Midpoint and Trapezoidal Rules?

The error in the Midpoint Rule can be calculated using the formula |(b-a)^3*f''(c)| / 24*n^2, where a and b are the endpoints of the interval, f''(x) is the second derivative of the function, and n is the number of subintervals. The error in the Trapezoidal Rule can be calculated using |(b-a)^3*f''(c)| / 12*n^2. These formulas give an upper bound for the error.

4. Can the Midpoint and Trapezoidal Rules be used for any type of function?

Yes, the Midpoint and Trapezoidal Rules can be used for any continuous function. However, they may not be as accurate for functions with high curvature or sharp turns. In those cases, other numerical integration methods may be more appropriate.

5. How do I apply the Midpoint and Trapezoidal Rules in real-world situations?

The Midpoint and Trapezoidal Rules are commonly used in physics, engineering, and other scientific fields to calculate areas and volumes of irregular shapes. They can also be used to estimate the values of integrals in situations where the function cannot be easily integrated analytically. Most graphing calculators and computer software have built-in functions for using these rules.

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