This free course, Particle physics, will give you an overview of current concepts and theories in the field. You will learn about the fundamental components of matter – known as leptons and quarks – and the composite particles, such as protons and neutrons, which are composed of quarks. You will see that all particle reactions may be described in terms of one of two fundamental interactions, known as the strong and the weak interactions, responsible for binding particles together and allowing them to change type, respectively.
This OpenLearn science course was updated with the kind support of Dangoor Education340, the educational arm of The Exilarch's Foundation.
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 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 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.
Do you have a Casio fx-83 ES scientific calculator (or a compatible model) and want to learn how to use it? This free course, Using a scientific calculator, will help you to understand how to use the different facilities and functions and discover what a powerful tool this calculator can be!
This free course, Exploring data: graphs and numerical summaries, will introduce you to a number of ways of representing data graphically and of summarising data numerically. You will learn the uses for pie charts, bar charts, histograms and scatterplots. You will also be introduced to various ways of summarising data and methods for assessing location and dispersion.
This free course is an introduction to differentiation. Section 1 looks at gradients of graphs and introduces differentiation from first principles. Section 2 looks at finding derivatives of simple functions. Section 3 introduces rates of change by looking at real life situations. Section 4 looks at using the derivative of a function to deduce useful facts for sketching its graph. Section 5 covers the second derivative test, used to determine the nature of stationary points and ends by looking at rates of change, including the real-life situation, using differentiation to find acceleration.
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 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 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.
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.