If you won’t further your studies into a STEM discipline, then the tools and techniques in this post would not be terribly relevant for you. But for the aspiring STEM student, we are now going to do calculus with trigonometric functions and exponential functions.
The derivative of is an exceedingly challenging idea to compute without more technical tool of limits outside the high school syllabus. To conceive of a meaningful derivation sacrifices either rigour or intuitiveness. Nevertheless, for this post, I will present the intuitive idea that appeared to me as I lay in my bed, fast asleep.
Denote . Derivatives intuitively measures the gradient of the tangent to the curve. Therefore, in the diagram below, I have computed the gradient of the tangent to each point on the curve
. I colour-coded each point
using the gradient
at that point on a scale from very-red (i.e. gradient of
) to very-green (i.e. gradient of
). Hence, the graph goes from green to red, then back to green at the very end.

If now we plot the points of the new graph according to the colour-coding, the first quarter of the new graph lies in the top-half green section. The second and third quarters of the new graph lie in the bottom-half red section. And finally, the fourth quarter of the new graph lie in the top half-green section once again.
Recalling our discussions on trigonometric graphs, looks very much like the graph of
. This is, in fact, mathematically true.
Theorem 1. .
Proof. Omitted. Or relegated to a study in more advanced calculus. In the language of limits, we need to use the limit definition of the derivative to show that
Then the core result is proven using the limit
Remark 1. Strictly speaking, we have put the cart before the horse—I couldn’t colour the sine graph unless I already knew that the derivative of is
. Nevertheless, the goal of this post is to motivate the result, then relegating a formal proof elsewhere in the blog.
You might wonder—in that case, why not obtain all other derivatives in this manner? Other than the fact that I need to slave-drive ChatGPT harder than I already do, it turns out that the existing differentiation technology, if we accept them to remain true for non-polynomials, empowers us to obtain (almost) all of these other derivatives.
For instance, the chain rule helps us compute the derivative of , since the complementary angle identities tell us that
Example 1. Show that .
Solution. Using the complementary angle identities, the chain rule, and Theorem 1,
These two results, coupled with the quotient rule, help us compute the derivative of , since
. These reasons and more motivated our study on trigonometric identities.
Example 2. Show that .
Solution. Using the quotient rule and previous theorems,
There are many more commonly-used derivatives in this exercise here. We now state the integral versions of these three results.
Theorem 4. The following integrals hold:
Proof. We prove the first result to illustrate the power of thinking of integration as reverse differentiation. Using Theorem 2 and linearity,
Therefore dividing by on both sides,
where .
We have to discuss the exponential family too. Once again, just like with the derivative of , the derivative of
requires more technical real-analytic tools to properly establish. Nevertheless, here is an experimentally-inspired attempt at motivating the result.
Let’s first ask ourselves: how can we experimentally compute the gradient of the tangent
at a point
on the graph of
? By definition, this tangent must pass through the point
.

Draw a line parallel to the tangent passing through
. We leave it as an exercise to check that its
-intercept
is given by the expression
In particular, if we know that has an
-intercept of
, then we can compute
via
Now particularise to , which we can draw by sampling input values:

Notice that the -intercept of
is exactly
. This result is not a bug—it’s a feature of the graph of
, and it works for any
. In particular, using our “experimental” calculation of
, we get
This result is a consequence of the famous differentiation result for exponentials.
Theorem 2. .
Proof. Omitted.
Remark 2. Once again, we have assumed Theorem 2 in our illustration. A complete proof requires a rigorous definition of the real exponential, then deducing its various properties, and concluding by using the limit definition of the derivative. In the language of limits, the heart of the proof is the limit result
Recall that has a foil: the logarithm. More precisely, whenever well-defined,
Example 3. Show that for
. The domain restriction
allows the expression
to make sense.
Solution. Using the chain rule and Theorem 2,
Remark 1. For , we have
, so the chain rule yields
Therefore, the integral version of these results are given by
Since the absolute value is defined by
we can abbreviate the integral result as follows:
In particular, the absolute value symbol is essential in our final answer.
Definition 1. Define for
by
Similarly, define for
by
Likewise, define for real
by
In particular,
The domain restrictions allow the expressions ,
,
to make sense, similar to how the domain restriction
allows the expression
to make sense.
Example 4. Show that .
Solution. For the first result, use the chain rule and Theorem 1:
Since ,
, so that
.
By the Pythagorean identity,
Therefore,
By definition,
Example 5. Show that .
Solution. Follow the strategy in Example 4 by using the chain rule and Example 2:
Using the Pythagorean identity,
Therefore,
By definition,
We conclude with one rather peculiar result regarding .
Example 6. Given that , show that
Solution. By the complementary angle identities,
Differentiating on both sides,
We have barely scratched the surface of calculus. There is much more that can be explored in many depths. At a high level, the area interpretation of integration allows mathematicians and statisticians to model probabilities—our conceived notions of randomness. We explore a special sub-branch of this topic next time.
—Joel Kindiak, 23 Jan 26, 2045H
Leave a comment