# Thoughts on Numerical Integration (Part 6): Connection between Simpson’s Rule, Trapezoid Rule, and Midpoint Rule

Numerical integration is a standard topic in first-semester calculus. From time to time, I have received questions from students on various aspects of this topic, including:
• Why is numerical integration necessary in the first place?
• Where do these formulas come from (especially Simpson’s Rule)?
• How can I do all of these formulas quickly?
• Is there a reason why the Midpoint Rule is better than the Trapezoid Rule?
• Is there a reason why both the Midpoint Rule and the Trapezoid Rule converge quadratically?
• Is there a reason why Simpson’s Rule converges like the fourth power of the number of subintervals?
In this series, I hope to answer these questions. While these are standard questions in a introductory college course in numerical analysis, and full and rigorous proofs can be found on Wikipedia and Mathworld, I will approach these questions from the point of view of a bright student who is currently enrolled in calculus and hasn’t yet taken real analysis or numerical analysis.
In the previous post in this series, I discussed three different ways of numerically approximating the definite integral $\displaystyle \int_a^b f(x) \, dx$, the area under a curve $f(x)$ between $x=a$ and $x=b$. In this series, we’ll choose equal-sized subintervals of the interval $[a,b]$. If $h = (b-a)/n$ is the width of each subinterval so that $x_k = x_0 + kh$, then the integral may be approximated as

$\int_a^b f(x) \, dx \approx h \left[f(x_0) + f(x_1) + \dots + f(x_{n-1}) \right] \equiv L_n$

using left endpoints,

$\int_a^b f(x) \, dx \approx h \left[f(x_1) + f(x_2) + \dots + f(x_n) \right] \equiv R_n$

using right endpoints, and

$\int_a^b f(x) \, dx \approx h \left[f(c_1) + f(c_2) + \dots + f(c_n) \right] \equiv M_n$

using the midpoints of the subintervals. We have also derived the Trapezoid Rule

$\int_a^b f(x) \, dx \approx \displaystyle \frac{h}{2} [f(x_0) + 2f(x_1) + \dots + 2f(x_{n-1}) + f(x_n)] \equiv T_n$

and Simpson’s Rule (if $n$ is even)

$\int_a^b f(x) \, dx \approx \displaystyle \frac{h}{3} \left[y_0 + 4 y_1 + 2 y_2 + 4 y_3 + \dots + 2y_{n-2} + 4 y_{n-1} + y_{n} \right] \equiv S_n$.

There is a somewhat surprising connection between the last three formulas. Let’s divide the interval $[a,b]$ into $2n$ subintervals with $h = (b-a)/(2n)$ and $x_0 = a$, $x_1 = x_0 + h$, $x_2 = x_0 + 2h$, and so on. Then Simpson’s Rule becomes

$S_{2n} = \displaystyle \frac{h}{3} \left[y_0 + 4 y_1 + 2 y_2 + 4 y_3 + \dots + 2y_{2n-2} + 4 y_{2n-1} + y_{2n} \right]$.

Next, let’s divide the interval $[a,b]$ into $n$ subintervals, but let’s not redefine the values of $h$ and the $x_k$. Instead, the width of each subinterval will be $(b-a)/n$, which is equal to $2h$. (In other words, since there are half as many subintervals, each one is twice as long.) Also, the endpoints of these subintervals will be $x_0 = a$, $x_2 = x_0 + 2h$, $x_4 = x_0 + 4h$, and so on. So, keeping the same labeling convention as with Simpson’s Rule, the Trapezoid Rule becomes

$T_n = \displaystyle \frac{2h}{2} [f(x_0) + 2f(x_2) + 2f(x_4) + \dots + 2f(x_{2n-2}) + f(x_{2n})]$

$= h [f(x_0) + 2f(x_2) + 2f(x_4) + \dots + 2f(x_{2n-2}) + f(x_{2n})]$.

(Again, the width of the subintervals in this case is $2h$, where $h = (b-a)/2n$.) Furthermore, the midpoint of subinterval $[x_0, x_2]$ will be $x_1$, the midpoint of subinterval $[x_2,x_4]$ will be $x_3$, and so on. Therefore, keeping the same labeling convention, the Midpoint Rule becomes

$M_n = \displaystyle 2h [f(x_1) + f(x_3) + f(x_5) + \dots + f(x_{2n-1}) ]$.

It turns out that $\displaystyle \frac{2}{3} M_n + \frac{1}{3} T_n$, a certain weighted average of $T_n$ and $M_n$, is equal to

$\displaystyle \frac{4h}{3} [f(x_1) + f(x_3) + \dots + f(x_{2n-1}) ] + \frac{h}{3} [f(x_0) + 2f(x_2) + \dots + 2f(x_{2n-2}) + f(x_{2n})]$

$= \displaystyle \frac{h}{3} [f(x_0) + 4 f(x_1) + 2f(x_2) + \dots + 2f(x_{2n-2}) + 4 f(x_{2n-1} + f(x_{2n})]$

$= S_{2n}$.

So, if the Midpoint Rule and the Trapezoid Rule have already been computed for $n$ subintervals, then Simpson’s Rule for $2n$ subintervals can be computed at almost no additional effort.

# Engaging students: Using a recursively defined sequence

In my capstone class for future secondary math teachers, I ask my students to come up with ideas for engaging their students with different topics in the secondary mathematics curriculum. In other words, the point of the assignment was not to devise a full-blown lesson plan on this topic. Instead, I asked my students to think about three different ways of getting their students interested in the topic in the first place.

I plan to share some of the best of these ideas on this blog (after asking my students’ permission, of course).

This student submission comes from my former student Enrique Alegria. His topic, from Precalculus: using a recursively defined sequence.

How can this topic be used in your students’ future courses in mathematics or science?

Recursion is heavily emphasized within the branches of computer science. The technique can be used more than just in arithmetic and geometric sequences for finding the next term. Within computer science, recursion techniques can be utilized for sorting algorithms. The content will be able to transfer easily. Instead of finding the previous term to use to find the current term, within sorting algorithms, a set of numbers is chunked into smaller and smaller sets such that the original set of numbers becomes sorted.

We can take a deeper look at Merge Sort which is a recursive sorting algorithm. What occurs is the set of numbers repeatedly gets cut in half until there is only one element in the list. From there the elements are sorted in increasing order. Traversing back into the original size of the list with all of the elements contained except the final output is the list in increasing order.

Students can inspect the algorithm visually and need not to understand the implementation of code to comprehend the functionality of recursion. Guiding the students towards the smallest part of the process which is the single element and from there rearranging the elements of the list.

How has this topic appeared in high culture (art, classical music, theatre, etc.)?

Recursively defined sequences influenced a renowned artist who is M.C. Escher. The concept of a sequence beginning at one point and continuing infinitely is how Escher exhibits recursion. Escher challenges the viewer of his work to determine the patterns from the artistic series.

For example, when observing the piece Drawing Hands, a student can predict what the ‘base case’ of the artwork would be followed by the next steps of the drawing. The spectator of this piece can break it apart into smaller and smaller partitions of the whole. And once they reach a starting point, they can put together the whole picture once again.

Similarly, students can view this piece titled Two Birds to follow the patterns. Without saying the name of the piece students can again predict the base case and determine how recursion techniques would be used for this sequence. Students can begin to learn how to think of how recursively defined sequences are applied through visual representations of M.C. Escher’s artwork.

How can technology be used to effectively engage students with this topic?

Technology can be used to effectively engage students with recursion by showcasing the YouTube video “Recursion: The Music Videos of Michel Gondry” by Polyphonic. Through this video, students can compare recursively defined sequences to music they listen to. The video starts with singular notes and then repeating the notes to create a rhythm. Compiling the initial sounds into something familiar through loops of samples and sound bites. This video goes into the repetitive patterns of the small chunks of sound are shown through visual representations with the music videos by Michel Gondry. In the music video “Star Guitar” by The Chemical Brothers, the video starts off with the listener on a train ride going through a landscape. Slowly patterns emerge as buildings uniquely correspond to the notes and rhythms within the song. With this YouTube video students obtain a great introduction to recursion and hopefully continue to find patterns of recursion to music they listen to in the future.

References

Greenberg I., Xu D., Kumar D. (2013) Drawing with Recursion. In: Processing. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4302-4465-3_8

Miller, B., & Ranum, D. (2020). 6.11. The Merge Sort — Problem Solving with Algorithms and Data Structures. Runestone.academy. https://runestone.academy/runestone/books/published/pythonds/SortSearch/TheMergeSort.html.

# Thoughts on Numerical Integration (Part 5): Derivation of Simpson’s Rule

Numerical integration is a standard topic in first-semester calculus. From time to time, I have received questions from students on various aspects of this topic, including:

• Why is numerical integration necessary in the first place?
• Where do these formulas come from (especially Simpson’s Rule)?
• How can I do all of these formulas quickly?
• Is there a reason why the Midpoint Rule is better than the Trapezoid Rule?
• Is there a reason why both the Midpoint Rule and the Trapezoid Rule converge quadratically?
• Is there a reason why Simpson’s Rule converges like the fourth power of the number of subintervals?

In this series, I hope to answer these questions. While these are standard questions in a introductory college course in numerical analysis, and full and rigorous proofs can be found on Wikipedia and Mathworld, I will approach these questions from the point of view of a bright student who is currently enrolled in calculus and hasn’t yet taken real analysis or numerical analysis.

In the previous post in this series, I discussed three different ways of numerically approximating the definite integral $\displaystyle \int_a^b f(x) \, dx$, the area under a curve $f(x)$ between $x=a$ and $x=b$.

In this series, we’ll choose equal-sized subintervals of the interval $[a,b]$. If $h = (b-a)/n$ is the width of each subinterval so that $x_k = x_0 + kh$, then the integral may be approximated as

$\int_a^b f(x) \, dx \approx h \left[f(x_0) + f(x_1) + \dots + f(x_{n-1}) \right] \equiv L_n$

using left endpoints,

$\int_a^b f(x) \, dx \approx h \left[f(x_1) + f(x_2) + \dots + f(x_n) \right] \equiv R_n$

using right endpoints, and

$\int_a^b f(x) \, dx \approx h \left[f(c_1) + f(c_2) + \dots + f(c_n) \right] \equiv M_n$

using the midpoints of the subintervals. We have also derived the Trapezoid Rule:

$\int_a^b f(x) \, dx \approx \displaystyle \frac{h}{2} [f(x_0) + 2f(x_1) + \dots + 2f(x_{n-1}) + f(x_n)] \equiv T_n$

This last approximation was obtained by connecting adjacent points on the curve by line segments, creating trapezoids:

In this post, we will derive Simpson’s Rule. Instead of connecting two adjacent points with line segments, we will connect three adjacent points with a parabola. In the picture below, the points $(x_0, f(x_0))$, $(x_1, f(x_1))$ and $(x_2,f(x_2))$ are connected with one parabola, while the points $(x_2, f(x_2))$, $(x_3, f(x_3))$ and $(x_4,f(x_4))$ are connected with a different second parabola.

Clearly, for this to work, there has to be an even number of subintervals. (By contrast, for the Trapezoid Rule, the Midpoint Rule, or the endpoint rules, the number of subintervals could be even or odd.)

The derivation of Simpson’s Rule is more complicated than the derivation of the Trapezoid Rule because we need to use calculus to find the area under these parabolas. To begin, we make the simplifying assumption that $x_1 = 0$. Since each subinterval has width $h$, this means that $x_0 = -h$ and $x_2 = h$.

To find the area under this parabola, we first need to find the equation of the parabola $y = ax^2 + bx + c$ connecting the three points $(-h,y_0)$, $(0,y_1)$, and $(h,y_2)$. This entails solving a system of three equations in three unknowns:

$a(-h)^2 + b(-h) + c = y_0$

$a(0)^2+b(0) + c = y_1$

$ah^2 + bh + c = y_2$,

or

$ah^2 - bh + c = y_0$

$c = y_1$

$ah^2 + bh + c = y_2$.

While most 3×3 systems are cumbersome to solve, this system is straightforward. Clearly, $c = y_1$. Also, subtracting the first equation from the third equation yields

$2bh = y_2 - y_0$, or $b = \displaystyle \frac{y_2 - y_0}{2h}$

Finally, we solve for $a$ by substituting into the third equation:

$ah^2 + \displaystyle \frac{y_2 - y_0}{2h} h + y_1 = y_2$

$ah^2 + \displaystyle \frac{y_2 - y_0}{2} + y_1 = y_2$

$ah^2 = \displaystyle \frac{y_0 - y_2}{2} - \frac{2y_1}{2} + \frac{2y_2}{2}$

$ah^2 = \displaystyle \frac{y_0 - 2y_1 + y_2}{2}$

$a = \displaystyle \frac{y_0 - 2y_1 + y_2}{2h^2}$

Next, we find the integral of $y = ax^2 + bx + c$ between $x = -h$ and $x = h$:

$\displaystyle \int_{-h}^h (ax^2 + bx + c) \, dx = \left[ \frac{ax^3}{3} + \frac{bx^2}{2} + cx \right]^h_{-h}$

$= \displaystyle \left[ \frac{ah^3}{3} + \frac{bh^2}{2} + ch \right] - \left[ -\frac{ah^3}{3} + \frac{bh^2}{2} - ch \right]$

$= \displaystyle \frac{2ah^3}{3} + 2ch$

$= \displaystyle \frac{(y_0 - 2y_1 + y_2)h}{3} + 2y_1h$

$= \displaystyle \frac{h(y_0 + 4y_1 + y_2)}{3}$.

We now turn to the more general case of finding the area under the parabola passing through $(x_0,y_0)$, $(x_1,y_1)$, and $(x_2,y_2)$, where $x_1 = x_0 +h$ and $x_2 = x_1 + 2h$. Geometrically, it should be clear that this parabola can be obtained from the above parabola by a horizontal translation. Since the area under the curve is not changed by a horizontal translation, the area (and the formula) will be the same.

More formally, if $y = ax^2 + bx + c$ passes through the points $(-h,y_0)$, $(0,y_1)$, and $(h,y_2)$, then $y = a(x-x_1)^2 + b(x-x_1) + c$ will pass through the points $(x_0,y_0)$, $(x_1,y_1)$, and $(x_2,y_2)$. The area under this curve is

$\displaystyle \int_{x_0}^{x_2} \left[ a(x-x_1)^2 + b(x-x_1) + c \right] \, dx$.

After using the substitution $u = x-x_1$, this becomes

$\displaystyle \int_{-h}^h (au^2 + bu + c) \, du$,

which is the same integral that we saw earlier. Therefore,

$\displaystyle \int_{x_0}^{x_2} \left[ a(x-x_1)^2 + b(x-x_1) + c \right] \, dx = \displaystyle \frac{h(y_0 + 4y_1 + y_2)}{3}$.

Finally, we need to find the sum of the areas under all of these parabolas. Similarly, the area under the parabola passing through $(x_2,y_2)$, $(x_3,y_3)$, and $(x_4,y_4)$ will be $\displaystyle \frac{h(y_2 + 4y_3 + y_4)}{3}$. So, for the particular example shown above, the total area under the parabolas will be

$\displaystyle \frac{h(y_0 + 4y_1 + y_2)}{3} + \frac{h(y_2 + 4y_3 + y_4)}{3} = \frac{h}{3} (y_0 + 4 y_1 + 2 y_2 + 4 y_3 + y_4)$.

The coefficients of 4 arose from the above integrals, while the coefficient of 2 came from combining the two areas. In general, if there are $n$ subintervals and $n$ is even, then Simpson’s Rule gives the approximation

$S_n = \displaystyle \frac{h}{3} \left(y_0 + 4 y_1 + 2 y_2 + 4 y_3 + \dots + 2y_{n-2} + 4 y_{n-1} + y_{n} \right)$.

# Engaging students: Powers and exponents

In my capstone class for future secondary math teachers, I ask my students to come up with ideas for engaging their students with different topics in the secondary mathematics curriculum. In other words, the point of the assignment was not to devise a full-blown lesson plan on this topic. Instead, I asked my students to think about three different ways of getting their students interested in the topic in the first place.

I plan to share some of the best of these ideas on this blog (after asking my students’ permission, of course).

This student submission comes from my former student Austin Stone. His topic, from Pre-Algebra: powers and exponents.

What interesting (i.e., uncontrived) word problems using this topic can your students do now?

“The number of people who are infected with COVID-19 can double each day. If it does double every day, and one person was infected on day 0, how many people would be infected after 20 days?” This problem can be a current real-life word problem that all students can relate to given the times we are in. This problem would be a good introductory for students to see how quickly numbers can get when using exponents. This would be an engaging introductory to exponents and will get the students interested because they can easily see that this can be used in current problems facing the world. This problem could also work later in Algebra if you ask how many days it would take to infect “blank” amount of people. This makes the question more of a challenge because they would have to solve for “x” (days) which is the exponent.

How has this topic appeared in the news?

This topic has been the news so far in 2020 if we are being honest. COVID-19 is a virus that has an exponential infection rate, just like any virus. When talking about COVID-19, news reporters and doctors usually use graphs to depict the infection rate. These graphs start off small but then grow exponentially until it slows down due to either people being more aware of their hygiene habits and/or the human immune system getting more familiar with the virus. Knowing how exponents work helps people better understand the seriousness of viruses such as COVID-19 and the everlasting impact it can have on the world. Doctors study what are the best ways to slow down the exponential growth so that a limited number of people contract and potentially die from the virus. To do this, they predict the exponential growth keeping in mind the regulations that may be enforced. Whatever regulation(s) slow down the virus the most are the ones that they try to enforce.

How can technology (YouTube, Khan Academy [khanacademy.org], Vi Hart, Geometers Sketchpad, graphing calculators, etc.) be used to effectively engage students with this topic?

An easy way to introduce students who have never seen exponents or exponential growth before is to use a graphing calculator. By plugging in an exponential function into the calculator and viewing the graph and zooming out, students can easily see how quickly numbers start to get massively large. A teacher can set this up by giving the students a problem to think about such as, “how many people would be infected with the virus after “blank” amount of day?” Students then could guess what they believe it would be. After revealing the graph and the actual number, students will probably be surprised at how big the number is in just a short amount of time. After that, the teacher could show a video on YouTube about exponential growth and/or infection rates of viruses and how quickly a small virus can turn into a pandemic. This also has very current real-world applications.

# Thoughts on Numerical Integration (Part 4): Derivation of Trapezoid Rule

Numerical integration is a standard topic in first-semester calculus. From time to time, I have received questions from students on various aspects of this topic, including:

• Why is numerical integration necessary in the first place?
• Where do these formulas come from (especially Simpson’s Rule)?
• How can I do all of these formulas quickly?
• Is there a reason why the Midpoint Rule is better than the Trapezoid Rule?
• Is there a reason why both the Midpoint Rule and the Trapezoid Rule converge quadratically?
• Is there a reason why Simpson’s Rule converges like the fourth power of the number of subintervals?

In this series, I hope to answer these questions. While these are standard questions in a introductory college course in numerical analysis, and full and rigorous proofs can be found on Wikipedia and Mathworld, I will approach these questions from the point of view of a bright student who is currently enrolled in calculus and hasn’t yet taken real analysis or numerical analysis.

In the previous post in this series, I discussed three different ways of numerically approximating the definite integral $\displaystyle \int_a^b f(x) \, dx$, the area under a curve $f(x)$ between $x=a$ and $x=b$.

In this series, we’ll choose equal-sized subintervals of the interval $[a,b]$. If $h = (b-a)/n$ is the width of each subinterval so that $x_k = x_0 + kh$, then the integral may be approximated as

$\int_a^b f(x) \, dx \approx h \left[f(x_0) + f(x_1) + \dots + f(x_{n-1}) \right] \equiv L_n$

using left endpoints,

$\int_a^b f(x) \, dx \approx h \left[f(x_1) + f(x_2) + \dots + f(x_n) \right] \equiv R_n$

using right endpoints, and

$\int_a^b f(x) \, dx \approx h \left[f(c_1) + f(c_2) + \dots + f(c_n) \right] \equiv M_n$

using the midpoints of the subintervals.

All three of these approximations were obtained by approximating the above shaded region by rectangles. However, perhaps it might be better to use some other shape besides rectangles. In the Trapezoidal Rule, we approximate the area by using (surprise!) trapezoids, as in the figure below.

The first trapezoid has height $h$ and bases $f(x_0)$ and $f(x_1)$, and so the area of the first trapezoid is $\frac{1}{2} h[ f(x_0) + f(x_1) ]$. The other areas are found similarly. Adding these together, we get the approximation

$T_n = \displaystyle \frac{h}{2}[f(x_0) + f(x_1)] + \frac{h}{2} [f(x_1) + f(x_2)] + \dots +$

$+ \displaystyle \frac{h}{2} [f(x_{n-2})+f(x_{n-1})] + \frac{h}{2} [f(x_{n-1})+f(x_n)]$

$= \displaystyle \frac{h}{2} [f(x_0) + 2f(x_1) + 2f(x_2) + \dots + 2f(x_{n-2}) + 2f(x_{n-1}) + f(x_n)].$

Interestingly, $T_n$ is the average of the two endpoint approximations $L_n$ and $R_n$:

$\displaystyle \frac{L_n+R_n}{2} = \frac{L_n}{2} + \frac{R_n}{2}$

$= \displaystyle \frac{h}{2} \left[f(x_0) + f(x_1) + f(x_2) + \dots + f(x_{n-1}) \right]$

$+\displaystyle \frac{h}{2} \left[f(x_1) + f(x_2) + \dots + f(x_{n-1}) + f(x_{n}) \right]$

$= \displaystyle \frac{h}{2} \left[f(x_0) + 2f(x_1) + \dots + 2f(x_{n-1}) + f(x_n) \right]$

$= T_n$.

Of course, as a matter of computation, it’s a lot quicker to directly compute $T_n$ instead of computing $L_n$ and $R_n$ separately and then averaging.

# Engaging students: Using Pascal’s triangle

In my capstone class for future secondary math teachers, I ask my students to come up with ideas for engaging their students with different topics in the secondary mathematics curriculum. In other words, the point of the assignment was not to devise a full-blown lesson plan on this topic. Instead, I asked my students to think about three different ways of getting their students interested in the topic in the first place.

I plan to share some of the best of these ideas on this blog (after asking my students’ permission, of course).

This student submission comes from my former student Jaeda Ransom. Her topic, from Precalculus: using Pascal’s triangle.

How could you as a teacher create an activity or project that involves your topic?

A great activity that involves Pascal’s Triangle would be the sticky note triangle activity. For this activity students will be recreating an enlarged version of Pascal’s Triangle. To complete this activity students will need a poster of Pascal’s Triangle, poster board, markers, sticky notes, classroom wall (optional), and tape (optional). The teacher’s role is to show students Pascal’s Triangle, along with an explanation of how it was made. Students will be working in pairs and grabbing the necessary materials needed to complete this activity.On the poster board the students will recreate Pascal’s Triangle. Students will write a number 1 on a sticky note and place it at the top of the posterboard, they will then write 2 number 1’s on a sticky note and place it directly under. The students will continue recreating the triangle on their poster board until they run out of space. You can also consider having students use smaller sticky notes so that students are engaged with creating more rows.

What interesting things can you say about the people who contributed to the discovery and/or the development of this topic?

Pascal’s Triangle was named after French mathematician Blaise Pascal. At just the age of 16 years old Pascal wrote a significant treatise on the subject of projective geometry marking him as a child prodigy. Amongst that, Pascal also corresponded with other mathematicians on probability theory, which vastly encouraged the development of modern economics and social science. Pascal was also one of the first two inventors of the mechanical calculator when he started pioneering work on calculating machines, these were called Pascal’s calculators and later Pascalines. Pascal impressively created and invented all of this as a teenager. Though the Pascal Triangle was named after Blaise Pascal, this theory was established well before Pascal in India, Persia, China, Germany, and Italy. As a matter of fact, in China they still call it the Yang Hui’s triangle, named after Chinese mathematician Yang Hui who presented the triangle in the 13th century, though the triangle was known in China since the early 11th century.

How can this topic be used in your students’ future courses in mathematics or science?

This topic can be used in my students future mathematics course to introduce binomial expansions, where it is known that Pascal’s Triangle determines the coefficients that arise in binomial expansion. The coefficients aᵢ in a binomial expansion represents the number of row n in the Pascal’s Triangle. Thus, $a_i = \displaystyle {n \choose i}$.

Another useful application of this topic is in the calculations of combinations. The equation to find the combination is also the formula to find a cell for Pascal’s Triangle. So, instead of performing the calculations using the equation a student can simply use Pascal’s Triangle. In doing this you can continue a lesson over probability or even do an activity using Pascal’s Triangle while implicating probability questions.

Resources:

https://en.wikipedia.org/wiki/Pascal%27s_triangle#Formula

# Thoughts on Numerical Integration (Part 3): Derivation of left, right, and midpoint rules

Numerical integration is a standard topic in first-semester calculus. From time to time, I have received questions from students on various aspects of this topic, including:

• Why is numerical integration necessary in the first place?
• Where do these formulas come from (especially Simpson’s Rule)?
• How can I do all of these formulas quickly?
• Is there a reason why the Midpoint Rule is better than the Trapezoid Rule?
• Is there a reason why both the Midpoint Rule and the Trapezoid Rule converge quadratically?
• Is there a reason why Simpson’s Rule converges like the fourth power of the number of subintervals?

In this series, I hope to answer these questions. While these are standard questions in a introductory college course in numerical analysis, and full and rigorous proofs can be found on Wikipedia and Mathworld, I will approach these questions from the point of view of a bright student who is currently enrolled in calculus and hasn’t yet taken real analysis or numerical analysis.

For the sake of completeness, I discuss here the origins of the left-endpoint, right-endpoint, and midpoint rules of numerical integration. (These topics are often presented in calculus texts.) Consider the problem of finding $\displaystyle \int_a^b f(x) \, dx$, the area under a curve $f(x)$ between $x=a$ and $x=b$.

To start the process of numerical integration, the interval $[a,b]$ is divided into subintervals. Usually, for convenience, the intervals are chosen to be the same length, a convention that I’ll follow in this series. That said, if the function is known to vary wildly on some parts of the domain but not so wildly on other parts, then computational efficiency can be gained by varying the sizes of the subintervals, choosing smaller subintervals for the places where the function varies wildly.

In any event, we’ll choose equal-sized subintervals for the duration of this series.

One numerical approximation can be made by choosing left endpoints. In the picture below, the interval $[a,b]$ was divided into four equal subintervals. Let $h = (b-a)/4$, so that $x_0 = a$, $x_1 = x_0 +h$, $x_2 = x_0 + 2h$, $x_3 = x_0 + 3h$, and $x_4 = x_0 + 4h = b$. We then can draw rectangles using the left endpoints of each subinterval. The sum of the areas of these rectangles below is

$hf(x_0) + hf(x_1) + hf(x_2) +hf(x_3)$,

and so this serves as an approximation to the area under the curve. In general, if there are $n$ subintervals and $x_k = x_0 + kh$, then the integral may be approximated as

$\int_a^b f(x) \, dx \approx h \left[f(x_0) + f(x_1) + \dots + f(x_{n-1}) \right]$

That said, left endpoints were not necessary for making an approximation. We could have instead chosen the right endpoints of each subinterval. The sum of the areas of the rectangles below is

$hf(x_1) + hf(x_2) + hf(x_3) +hf(x_4)$,

and so this serves as an approximation to the area under the curve. In general, if there are $n$ subintervals, then the integral may be approximated as

$\int_a^b f(x) \, dx \approx h \left[f(x_1) + f(x_2) + \dots + f(x_n) \right]$

As a final approximation, any point in each subinterval could’ve been used for making an approximation. In the picture below, we use the midpoints of the subintervals, where $c_k = (x_k + x_{k-1})/2$. The sum of the areas of the rectangles below is

$hf(c_1) + hf(c_2) + hf(c_3) +hf(c_4)$,

and so this serves as an approximation to the area under the curve. In general, if there are $n$ subintervals, then the integral may be approximated as

$\int_a^b f(x) \, dx \approx h \left[f(c_1) + f(c_2) + \dots + f(c_n) \right]$

# Engaging students: Synthetic Division

In my capstone class for future secondary math teachers, I ask my students to come up with ideas for engaging their students with different topics in the secondary mathematics curriculum. In other words, the point of the assignment was not to devise a full-blown lesson plan on this topic. Instead, I asked my students to think about three different ways of getting their students interested in the topic in the first place.

I plan to share some of the best of these ideas on this blog (after asking my students’ permission, of course).

This student submission comes from my former student Cire Jauregui. Her topic, from Precalculus: synthetic division.

How can technology (YouTube, Khan Academy [khanacademy.org], Vi Hart, Geometers Sketchpad, graphing calculators, etc.) be used to effectively engage students with this topic?

The website IXL has a series of Algebra 2 learning topics where students can do practice problems. It presents students with a problem and tracks how long it takes them to solve the question. It also gives them a score out of 100. This site also has examples students can use to help them learn. The “Learn with an example” page walks students through the process step by step so that they can learn the process. If a student answers correctly, they are congratulated, given points, and then given a new problem to solve. If a student answers the question incorrectly, they are given a full explanation with the steps to solve the problem written out so students can check where they messed up. There are so many problems this program can come up with and provide students with many examples of all kinds.

What interesting things can you say about the people who contributed to the discovery and/or the development of this topic?

Paolo Ruffini developed Ruffini’s rule which is now known most commonly as synthetic division. Ruffini was an Italian mathematician in the late 1700s. In 1796, Napoleon Bonaparte and his troops signed agreements with the duke of Modena where Ruffini was studying and teaching. Here Napoleon set up the Cisalpine Republic where Ruffini was appointed to be a representative for the Junior Council of the Cisalpine Republic. He did not wish to take the position, so he left to return to his studies at the University of Modena in 1798. However, when he was required to swear an oath to the Republic, Ruffini refused due to his religious grounds and was removed from his teaching position at the university and told he could not teach again.

How does this topic extend what your students should have learned in previous courses?

This topic extends on a student’s ability to do long division and also polynomial long division. Polynomial long division works exactly how students would expect dividing a polynomial would work. The polynomial dividend is under the bracket, the leading term (not just the coefficient) of the divisor is used as the primary divisor which determines what should be on top of the bracket. This process continues until the divisor cannot divide into the dividend and then is used as a remainder where the “leftover” part is put over the divisor and left as a fraction. Synthetic division simplifies this process by focusing on the coefficients of the polynomial being divided. By focusing on the coefficients, it can remove some of the confusion students face when trying to do polynomial division.

# HyFlex Teaching During the Pandemic (and Beyond?)

I’m happy to say that an article I wrote teaching last spring — when I had to negotiate teaching both in-person students and students who were participating remotely — was published in this month’s issue of MAA FOCUS. I hope that some of these thoughts might be helpful to somebody else who might be in this position for the Fall 2021 semester.

# Engaging students: Half-life

In my capstone class for future secondary math teachers, I ask my students to come up with ideas for engaging their students with different topics in the secondary mathematics curriculum. In other words, the point of the assignment was not to devise a full-blown lesson plan on this topic. Instead, I asked my students to think about three different ways of getting their students interested in the topic in the first place.

I plan to share some of the best of these ideas on this blog (after asking my students’ permission, of course).

This student submission comes from my former student Trenton Hicks. His topic: working with the half-life of a radioactive element.

How can this topic be used in you students’ future courses in mathematics or science?

The topic of half life is a direct intersection of math and chemistry. In addition to being a common precalculus problem, we see half life come up in radioactive decay in chemistry. Half life is a concept that extends all the way into upper college chemistry, physics, and even archaeology when it comes to carbon dating. If students use carbon dating to any extent, they can use half life to determine the age of organic material since carbon 14 is radioactive (Wood). Since half life has to due with nuclear chemistry, this can also tie into nuclear power, since half life is crucial in computations related to efficiency and nuclear engineering. Half life is a form of exponential decay. If students have a thorough understanding of half life, they can better understand other natural phenomena that exhibit properties that are consistent with exponential decay. These phenomena include RC circuits, atmospheric pressure, and toxicity.

In Chernobyl Ukraine, 1986, there was a disaster at a nuclear power plant that has had lasting effects on the environment, people, and culture. The initial explosion was harmful enough, as 2 people lost their lives. Furthermore, radiation leaked into the atmosphere, and it’s speculated that many individuals are suffering the health consequences. When this story first broke, it shook everyone, and scared people away from nuclear power. Lately, there was another documentary that came to light about the incident from HBO. Many people don’t know that the former power plant is still very dangerous to this day. Why? Because the highly radioactive byproducts of the meltdown have half lives that makes them stick around for quite a while. One particularly dangerous isotope, caesium 137, has a half life of about 30 years. This means that in 2016, about half of the caesium decayed. Half of the sheer amount of caesium that was leaked due to the meltdown is still an enormously dangerous amount. News and documentaries report that there’s still a massive constructive effort to contain the radiation. Showing these news stories to students will convey the importance of half life and give them a little bit of insight into how much care should be given to nuclear power.

Half life began as a model proposed by Rutherford in the late 1800’s and very early 1900’s. Rutherford discovered that radioactive decay would turn one element into another. This change happens at a rate that we recognize as exponential decay, hence the model we use is consistent with that idea. Rutherford’s work would soon earn him a Nobel Prize. Other disciplines have taken the idea of “half life,” and have created convincing arguments for how the universe behaves. For instance, toxicology uses half life to convey how potent a dose of toxin is versus long it takes for the body to metabolize the toxin. Another notable development is the blog post on the fs website (linked below) that discusses half lives in terms of how our brains retain information, as well as the information itself. Relaying that half life isn’t just a chemistry or math topic to students, and providing them with this history might just increase the half life on their retaining of the concept.

References:

Fs blog:

Half Life: The Decay of Knowledge and What to Do About It

Sources:
Author: Rachael Wood