During the second year of the Bachelor’s Applied Mathematics your knowledge of mathematics and its application potential will grow. The assignments and projects you work on become more realistic and complex.

Module 5: statistics and analysis

In this module you will learn to look for linear relationships in statistical data, using an advanced software package, SPSS. In the Mathematical statistics part of the module, you will learn much of the underlying theory. You will continue to develop your knowledge of basic mathematics in Analysis, Part 2 (having done Part 1 in module 2 of the first year). Also, you will learn how to orally present a mathematical topic. You will practice this with a mathematical topic that is new to you and to your audience, receiving feedback from your teacher and fellow students. The presentation topics are not related to any modules, or even to the curriculum, so everyone can really judge how clearly you present.

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Module 6: dynamic systems

Mathematical models often involve differential equations. Such models are called dynamic, because they show the relationship between the variables and their changes, whereas so-called static models only represent the variables. In this module you will study dynamic models from the perspective of differential equation, mathematical system theory and numerical aspects, making use of MATLAB software. In the team project you will create a model for a dynamic process of the body, such as walking or running or jumping. The challenge here is to capture in a model the combination of stability and movement that characterises that movement.

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Module 7: efficient algorithms for discrete structures

You will follow this module with students doing our Bachelor’s Technical Computer Science. You will be studying so-called discrete structures. As opposed to continuous structures, such as a collection of real numbers, these structures are about finite or countably infinite sets and variations thereon. The focus is on making calculations within such sets, such as finding the shortest path between a certain number of points and the links between those points. The computability and complexity of these calculations are important factors. You will use elements from abstract algebra, such as groups, rings and fields, as well as finite automata and Turing machines.

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Module 8: stochastic methods for operations management

You will follow parts of this module with students enrolled in our Bachelor’s Industrial Engineering & Management and Civil Engineering. As far as mathematics is concerned, this module is about Markov chains. These are stochastic models, or models in which outcomes depend on chance, and in which you go from state to state according to a given probability distribution, regardless of where you were in the past. These models find all sorts of applications, for example, in modelling queues. They also play a vital role in modelling and simulating complex stochastic systems. In your multidisciplinary project group, together with Civil Engineering and Industrial Engineering and Management students, you will learn how to use such models to make good decisions in practical situations in which change plays an important role, for example, logistics, a hospital environment or traffic.

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