# Numerical Integration

## Numerical Integration Revision

**Numerical Integration**

There are times when **algebraic **methods **(integration)** don’t allow you to find the area under a curve. **Numerical methods** can be then used for **definite integrals**.

Make sure you are happy with the following topics before continuing.

**Trapezium Rule**

To find an approximate area under a curve we can **split the area into multiple trapeziums** and then add the areas of these trapeziums together.

The area of each trapezium is given by the formula:

\Large{A=\dfrac{h}{2}(y_n+y_{n+1})}

Then the area represented by \int^{b}_{a} y\,dx is approximated by:

\Large{\int^{b}_{a} y\,dx \approx \dfrac{h}{2}[y_0+2(y_1+y_2+ ... + y_{n-1})+y_n]}

- \boldsymbol{n} is the number of
**intervals** - \boldsymbol{h} is the
**width**of each interval, where \boldsymbol{h=\dfrac{(b-a)}{n}} - \boldsymbol{y_0, y_1, ... , y_n} are the
**heights**of the sides of the trapeziums, these are obtained by substituting the appropriate x-values into the equation of the curve.

**Underestimates / Overestimates**

Naturally, when using approximation methods you will either get an **underestimate or overestimate** of the true value of the area. The shape of the curve dictates whether your approximation will an underestimate or overestimate.

If the slanted side of the trapeziums are **above **the curve then the approximation for the area will be an **overestimate **– this is the case for convex curves.

If the slanted side of the trapeziums are **below **the curve then the approximation for the area will be an **underestimate** – this is the case for concave curves.

**Upper and Lower Bounds **

The trapezium rule will give an **approximation between two bounds** for the area under a curve. These upper and lower bounds are found by considering **rectangular strips** that lie above and below the curve respectively.

One bound is found by **summing the areas of the rectangles** which meet f(x) with their **left **hand corner, using the formula:

\int^{b}_{a}f(x) \, dx \approx h[y_0+y_1+y_2+...+y_{n-1}]

The second bound is found by **summing the areas of the rectangles** which meet f(x) with their **right **hand corner, using the formula:

\int^{b}_{a} f(x) \, dx \approx h[y_1+y_2+y_3+...+y_{n}]

If you are calculating the bounds of a curve with a **turning point** you will need to use the formula for one bound on one side of the turning point and the formula for the other bound on the other side.

**Integration is the Limit of the Sum of Rectangles**

Using the **limit of the sum of rectangles** to find a definite integral uses a similar idea to **differentiating from first principles**.

Differentiating from first principles involves finding the **gradient **of a straight line between two points on a curve of an **interval**. As the interval, \delta x, gets smaller and smaller (\delta x \to 0), the gradient of this straight line gets closer to the gradient of the curve at these points.

We can use the area of rectangles to find the **definite integral** between two points:

The area of each rectangle is: \text{height} \times \text{width}=f(x)\times \delta x

So the approximate area under the curve is the sum of the areas of the rectangles, which is written as:

\Large{\sum ^{b}_{x=a+\delta x} f(x)\delta x}

Like with differentiation. **the smaller the intervals the more accurate the approximation**. Therefore, as \delta x \to 0 the sum of the area of the rectangles approaches the definite integral.

This can be written as:

\Large{\lim\limits_{\delta x\to0} \sum ^{b}_{a+\delta x} f(x)\delta x=\int^{b}_{a}f(x) \, dx}

**Example 1: ****Numerical Integration**

Find an approximate value for \int^{3}_{1}\sqrt{x^3+2} \, dx using 5 strips. Give your answer to 3 significant figures.

First the **width of each interval** needs to be calculated:

Therefore the x-values are x_0=1, x_1=1.4, x_2=1.8, x_3=2.2, x_4=2.6 and x_5=3.

We can work out the corresponding y-values (heights) using the equation given:

Finally, **substituting **the y-values into the formula: {\int^{b}_{a} y\,dx \approx \dfrac{h}{2}[y_0+2(y_1+y_2+ ... + y_{n-1})+y_n]}

**Example 2: ****Using More Intervals**

Using **more intervals** gives you more **accurate **approximations:

Use the trapezium rule to approximate the area of \int^{0.5}_{0}2x\cos{2x} \, dx to 3 decimal places, with n=2 and n=4.

For n=2, the **width **of each strip, h=\dfrac{0.5-0}{2}=0.25.

Therefore, x_0=0, x_1=0.25 and x_2=0.5

**Substituting **these values into the equation gives the y-values:

y_0=0, y_1=0.4387... and y_2=0.5403...

Then using these values for the **trapezium rule** formula:

For n=4, the width of each strip, h=\dfrac{0.5-0}{4}=0.125.

Therefore, x_0=0, x_1=0.125, x_2=0.25, x_3=0.375 and x_4=0.5

**Substituting **these values into the equation gives the y-values:

y_0=0, y_1=0.242..., y_2=0.4387..., y_3=0.548... and y_4=0.5403...

Then using these values for the **trapezium rule** formula:

**Comparing **this with the exact answer that can be found by using **integration by parts, **the exact value for this integral is 0.191 to 3 decimal places, so we can see that using n=4 gives us an answer which is **closer **to the actual area.

## Numerical Integration Example Questions

**Question 1: **Use the trapezium rule to estimate the value of \int^{3}_{1} \dfrac{(x^3+x^2-x+2)}{(x+3)} \, dx to 3 decimal places using 5 intervals.

**[4 marks]**

First we need to find the value of h:

h=\dfrac{3-1}{4}=0.4So the x-values are:

x_0=1, x_1=1.4, x_2=1.8, x_3=2.2, x_4=2.6 and x_5=3

Substituting these values into the equation gives the y-values:

Now using the trapezium rule formula:

\begin{aligned} \int^{3}_{1} \dfrac{(x^3+x^2-x+2)}{(x+3)} \, dx & \approx \dfrac{0.5}{2} [0.75+2(1.205455+1.931667+2.94+4.238571)+5.833333] \\ &= 5.443 \, (3 \text{ d.p.}) \end{aligned}

**Question 2: **Use the trapezium rule to estimate the value of \int^{2}_{-1} -x^3+16x+16 \, dx using 5 intervals.

Calculate \int^{2}_{-1} -x^3+16x+16 \, dx algebraically to decide whether your approximation was an underestimate or an overestimate.

**[6 marks]**

First we need to find the value of h:

h=\dfrac{2-(-1)}{5}=0.6So the x-values are:

x_0=-1, x_1=-0.4, x_2=0.2, x_3=0.8, x_4=1.4 and x_5=2

Substituting these values into the equation gives the y-values:

Now using the trapezium rule formula:

\begin{aligned} \int^{2}_{-1}-x^3+16x+16 \, dx &\approx \dfrac{0.6}{2}[1+2(9.664+19.192+28.288+35.656)+40] \\ &=67.98 \end{aligned}

Integrating Algebraically:

\begin{aligned} \int^{2}_{-1} -x^3+16x+16 \, dx &=[-\dfrac{x^4}{4}+8x^2+16x]^{2}_{-1} \\ &=[-\dfrac{(2)^4}{4}+8(2)^2+16(2)]-[-\dfrac{(-1)^4}{4}+8(-1)^2+16(-1)]\\&=68.25 \end{aligned}

So we can see that our approximation is an underestimate.

**Question 3:** Use the graph below of y=x^3-7x+1 to decide whether using the trapezium rule to estimate \int^{0}_{-2} x^3-7x+1 \, dx would be an underestimate or overestimate.

**[2 marks]**

Between -2 and 0, the shape of the curve is concave, therefore if the trapezium rule was used it would give an underestimate for the area under the curve.

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