The culmination point of the podcast well-defined & wonderful (for now, anyway) is the second part of the fundamental theorem. It combines the most important notions of the podcast so far: continuity, differentiation, and integration. We shall show that continuous functions on bounded and closed intervals always admit an anti-derivative. This anti-derivative is given as the integral of this function integrated with a variable right end point. The first and second part of the fundamental theorem lead to the substitution rule and the integration by parts formula. Finally we will also attempt to prove the second part of the fundamental theorem by providing the main tricks and glueing them together into one wonderful proof.

In this episode we are studying a first connection of differentiation and integration. More precisely, we will show that if a Riemann integrable function has an anti-derivative then the computation of the integral comes down to the evaluation of the anti-derivative. The proof provided uses a re-interpretation of the mean value theorem. A reorganisation of the terms involved in the statement of the mean value theorem leads to a relation of function evaluation and the integral of a step function with some height given by the derivative at some point of the function. A telescoping sum and a limit argument concludes the proof. 

This episode is focussing on a different sort of monotonicity compared to the notions we have used before. Here, we view the integral as a mapping assigning numbers to (Riemann integrable) functions. Monotonicity of the integral then means that non-negative functions are mapped to non-negative numbers. Or, in other words, if one function is smaller than another; their respective integrals can be compared the same way. In related contexts such mappings on functions are also called positive. As an application, we provide a fundamental inequality for the integral — a continuous variant of the triangle inequality: The modulus of the integral of a function is bounded above by integral of the modulus of the said function.

This episode is concerned with providing another class of functions that are Riemann integrable. This class will be monotone functions and are neither contained nor are supersets of the step functions or continuous functions we have identified to be Riemann integrable already. The idea of proof for the desired result in the current episode is the construction of tailored step functions smaller and bigger than the monotone function so that the integral of the difference of the constructed functions gets smaller if the maximal distance of the partition points does so.

In this episode, we introduce the class of Riemann integrable functions. At the heart of the definition lies the wish to extend the intuitive notion for the integral of step functions on closed and bounded intervals to functions for which one can approximate the area between the function's graph and the x-axis by areas of rectangles. We then discuss that all continuous functions on a closed and bounded interval are Riemann in fact integrable - a fact that heavily relies on the property of uniform continuity.

The present episode asks a new question: How can one compute the area under the function graph of a  real-valued function defined on an interval? It turns out that this question is not entirely trivial to answer. In order to have a first clear understanding of some pitfalls, we treat an elementary example case first: We discuss the notion of a step function. Then, the area under function graph — the Riemann integral — can be computed as a sum of certain rectangles. Before we embark to more challenging situations, we shall see that the so defined integral will be well-defined for step functions.

This episodes focusses on the mean value theorem and its consequences. One way of describing the mean value theorem  is that the average velocity must be attained at some point. Reading this fact somehow backwards tells us some thing about the average velocity given some information about the derivative. Indeed, monotonicity can be obtained if the derivative has only one sign; also a sufficient criterion for the existence of extreme values can be shown. Other consequences like the generalised mean value theorem of the theorem of Bernoulli—l’Hospital are mentioned; for the precise statements we refer to the lecture noted however.

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Having defined the derivative of a function in the previous episode, we now turn to properties of the derivative and of the function in connection to the derivative. This episode is concerned with a first theorem asserting as much, namely Rolle’s theorem. This theorem tells us that the derivative of a differentiable function has a zero as long as it assumes one value twice. A consequence of this will be the mean value theorem, the consequences of which we address in the next episode.

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A more global viewpoint of the concept of differentiability is when a whole function is differentiable everywhere. In this case, we can define a mapping assigning each point to the limit of the difference quotient at this point. This map is called the derivative of a function. It is then of interest how operations on functions like multiplications, additions, quotients, compositions, etc behave under computing the derivative. It turns out that one can show certain rules of differentiation, which are also touched upon in this episode.

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This episode is concerned with the concept of Differentiability. Roughly speaking, we seek a quantitative method to assess the change (or rate of change) of a function. For this we consider its slope and try to define a slope at every single point in the domain of said function. Wherever this works, we call the function differentiable at this point. It turns out this notion is equivalent to the function being reasonably enough approximated by affine functions.