Cyrsiau Mathemateg ar-lein am ddim

This free course is concerned with second-order differential equations. Section 1 introduces some basic principles and terminology. Sections 2 and 3 give methods for finding the general solutions to one broad class of differential equations, that is, linear constant-coefficient second-order differential equations. Section 2 covers homogeneous equations and Section 3 covers inhomogeneous equations. Section 4 explains how extra information can be used to help to select particular solutions that are appropriate in given situations. Section 5 looks at the phenomenon of resonance to gain insights into the solutions of inhomogeneous linear constant-coefficient second-order differential equations.

In this free course, An introduction to complex numbers, you will learn how complex numbers are defined, examine their geometric representation and then move on to looking at the methods for finding the nth roots of complex numbers and the solutions to simple polynominal equations.

This free course is concerned with moving objects, that is, dynamics. Section 1 introduces concepts like position, velocity and acceleration, which describe the way an object moves. Section 2 discusses Newton’s laws of motion, which predict the motion of an object when the forces acting on it are known. Section 3 shows how Newton’s second law of motion can be used to predict the motion of objects. Section 4 concerns modelling some of the forces that occur in nature, which enables more realistic situations to be analysed. Section 5 looks at motion in more than one dimension.

This free course examines the basic kinematics of two-dimensional fluid flows. Section 1 introduces the differential equations for pathlines and streamlines. Section 2 introduces a scalar field, called the stream function, which for an incompressible fluid provides an alternative method of modelling the flow and finding the streamlines. Sections 2 and 3 derive the stream functions for several simple two-dimensional flow types (the uniform flow, source, doublet and vortex), and suitable combinations of these are used to model more complicated flows. Section 4 introduces the idea of differentiation following the motion, and Euler’s equation is developed in Section 5.

This free course is an introduction to Number Theory. Section 1 provides a brief introduction to the kinds of problem that arise in Number Theory. Section 2 reviews and provides a more formal approach to a powerful method of proof, mathematical induction. Section 3 introduces and makes precise the key notion of divisibility. The Division Algorithm, concerning the division of one integer by another, is used. Its consequences, both practical and theoretical, make it a cornerstone of number theory. Section 4 explores some of the basic properties of the prime numbers and introduces the sieve of Eratosthenes.

This free course consolidates and builds on group theory studied at OU level 2 or equivalent. Section 1 describes how to construct a group called the direct product of two given groups, and then describes certain conditions under which a group can be regarded as the direct product of its subgroups. Section 2 describes the key properties of the structure of cyclic groups. Section 3 introduces the notion of a set of generators of a group and a set of relations among the generators. It then looks at a family of finite groups, the dicyclic groups.

This free course examines the formulation and solution of small linear programming problems. Section 1 deals with the formulation of linear programming models, describing how mathematical models of suitable real-world problems can be constructed. Section 2 looks at graphical representations of two-dimensional models, considers some theoretical implications and examines the graphical solution of such models. Section 3 introduces the simplex method for solving linear programming models and Section 4 uses matrix notation to formalize the simplex method.

This free course is concerned with modelling and estimation and looks in particular at the binomial distribution. Section 1 starts by defining probability, introduces relevant notation and briefly discusses basic properties of probabilities. The section concludes by considering some of the general features of and ideas about modelling discrete random variables. Section 2 looks at one particular probability model for discrete data, the binomial distribution. Section 3 investigates how data can be used to estimate the probability of success in a single Bernoulli trial and introduces maximum likelihood estimation.

This free course develops ideas about probability and random processes. Sections 1 and 2 introduce the fundamental ideas of random processes through a series of examples. Section 3 describes a model that is appropriate for events occurring ‘at random’ in such a way that their rate of occurrence remains constant. Section 4 derives the main results from Section 3. Section 5 introduces the multivariate Poisson process in which each event may be just one of several different types of event. Section 6 introduces the non-homogeneous Poisson process in which events occur at a rate that varies with time.

This free course looks at point estimation, that is, the estimation of the value of the parameter of a statistical model by a single number, a point estimate for the parameter. Section 1 develops some aspects of maximum likelihood estimation. In particular, you will find out how to obtain the maximum likelihood estimator of an unknown parameter, using calculus. You will need to do lots of differentiation in this section. Section 2 introduces a number of important properties of point estimation.

This free course is an introduction to Bayesian statistics. Section 1 discusses several ways of estimating probabilities. Section 2 reviews ideas of conditional probabilities and introduces Bayes’ theorem and its use in updating beliefs about a proposition, when data are observed, or information becomes available. Section 3 introduces the main ideas of the Bayesian inference process. The prior distribution summarises beliefs about the value of a parameter before data are observed. The likelihood function summarises information about a parameter contained in observed data and the posterior distribution represents what is known about a parameter after the data have been observed.

This free course is concerned with some of the statistical methods used in epidemiology and more widely in medical statistics. Section 1 introduces cohort studies in which individuals are classified according to their exposure and followed forward in time to evaluate disease outcomes. Section 2 looks at models for cohort studies. Section 3 introduces case-control studies in which individuals are selected according to their disease status and past exposures are then ascertained. Section 4 covers testing for no association in cohort studies and case-control studies.

This free course contains an introduction to metric spaces and continuity. The key idea is to use three particular properties of the Euclidean distance as the basis for defining what is meant by a general distance function, a metric. Section 1 introduces the idea of a metric space and shows how this concept allows us to generalise the notion of continuity. Section 2 develops the idea of sequences and convergence in metric spaces. Section 3 builds on the ideas from the first two sections to formulate a definition of continuity for functions between metric spaces.

Surfaces are a special class of topological spaces that crop up in many places in the world of mathematics. In this free course, you will learn to classify surfaces and will be introduced to such concepts as homeomorphism, orientability, the Euler characteristic and the classification theorem of compact surfaces.

This free course contains an introduction to rings and polynomials. We see that polynomial rings have many properties in common with the integers; for example, we can define a division algorithm, and this enables us to develop the analogue of the highest common factor for two polynomials. Section 1 explores the abstract definitions of a ring and a field. Sections 2 and 3 define polynomial rings where the coefficients of the polynomials are elements from a given field. Section 3 develops results concerning the divisibility of polynomials.

This free course, Interpreting data: Boxplots and tables, is concerned with two main topics. In Section 1, you will learn about another kind of graphical display, the boxplot. A boxplot is a fairly simple graphic, which displays certain summary statistics of a set of data. Boxplots are particularly useful for assessing quickly the location, dispersion, and symmetry or skewness of a set of data, and for making comparisons of these features in two or more data sets. Boxplots can also be useful for drawing attention to possible outliers in a data set. The other topic, which is covered in Sections 2 and 3, is that of dealing with data presented in tabular form. You are, no doubt, familiar with such tables: they are common in the media and in reports and other documents. Yet it is not always straightforward to see at first glance just what information a table of data is providing, and it often helps to carry out certain calculations and/or to draw appropriate graphs to make this clearer. In this free course, some other kinds of data tables and some different approaches are covered.

This free course, Working on your own mathematics, focuses on your initial encounters with research. It invites you to think about how perceptions of mathematics have influenced you in your prior learning, your teaching and the attitudes of learners.

This free course, Working mathematically, is aimed at teachers who wish to review how they go about the practice of teaching mathematics, those who are considering becoming mathematics teachers, or those who are studying mathematics courses and would like to understand more about the teaching and learning process.

This free course, Teaching mathematics, has been designed for non-specialist mathematics teachers of 8 to 14 year olds, teaching assistants, home schoolers and parents and draws on the established provision of mathematics education at the Open University. It can also be used as Continuing Professional Development by individuals or groups of teachers. The authors have many years’ experience of teaching mathematics in the classroom and in Initial and Continuing Teacher Education.

This free course looks at Babylonian mathematics. You will learn how a series of discoveries has enabled historians to decipher stone tablets and study the various techniques the Babylonians used for problem-solving and teaching. The Babylonian problem-solving skills have been described as remarkable and scribes of the time received a training far in advance of anything available in medieval Christian Europe 3000 years later.

The Egyptians are known for being ahead of their time in comparison to some civilisations that came after them. This free course, Egyptian mathematics, looks at how the Egyptians solved mathematical problems in everyday life and the technology they used. An understanding of this area has only been possible following the translation of the Rosetta Stone.

This free course looks at Scotsman John Napier, best known to for his treatise on Protestant religion. However, it was his interest in a completely different subject that radically altered the course of mathematics. After 40 years of dabbling in maths, he revealed his table of logarithms in the early 17th century.

Casgliad o adnoddau o bob un o brifysgolion Cymru i'ch helpu i ddechrau gydag addysg uwch.