Professional Training

Further Mathematics Year 13 course 2

edX, Online
Length
7 weeks
Next course start
Start anytime See details
Course delivery
Self-Paced Online
Length
7 weeks
Next course start
Start anytime See details
Course delivery
Self-Paced Online
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Course description

Further Mathematics Year 13 course 2: Applications of Differential Equations, Momentum, Work, Energy & Power, The Poisson Distribution, The Central Limit Theorem, Chi Squared Tests, Type I and II Errors

This course by Imperial College London is designed to help you develop the skills you need to succeed in your A-level further maths exams.

You will investigate key topic areas to gain a deeper understanding of the skills and techniques that you can apply throughout your A-level study. These skills include:

  • Fluency selecting and applying correct methods to answer with speed and efficiency
  • Confidence critically assessing mathematical methods and investigating ways to apply them
  • Problem solving analysing the ‘unfamiliar’ and identifying which skills and techniques you require to answer questions
  • Constructing mathematical argument using mathematical tools such as diagrams, graphs, logical deduction, mathematical symbols, mathematical language, construct mathematical argument and present precisely to others
  • Deep reasoning analysing and critiquing mathematical techniques, arguments, formulae and proofs to comprehend how they can be applied
  • Over eight modules, you will be introduced to
  • Simple harmonic motion and damped oscillations.
  • Impulse and momentum.
  • The work done by a constant and a variable force, kinetic and potential energy (both gravitational and elastic) conservation of energy, the work-energy principle, conservative and dissipative forces, power.
  • Oblique impact for elastic and inelastic collision in two dimensions.
  • The Poisson distribution, its properties, approximation to a binomial distribution and hypothesis testing.
  • The distribution of sample means and the central limit theorem.
  • Chi-squared tests, contingency tables, fitting a theoretical distribution and goodness of fit.
  • Type I and type II errors in statistical tests.
  • Your initial skillset will be extended to give a clear understanding of how background knowledge underpins the A -level further mathematics course. You’ll also be encouraged to consider how what you know fits into the wider mathematical world.

Upcoming start dates

1 start date available

Start anytime

  • Self-Paced Online
  • Online
  • English

Outcome / Qualification etc.

What you'll learn

  • How to derive and solve a second order differential equation that models simple harmonic motion.
  • How to derive a second order differential equation for damped oscillations.
  • The meaning of underdamping, critical damping and overdamping.
  • How to solve coupled differential equations.
  • How to calculate the impulse of one object on another in a collision.
  • How to use the principle of conservation of momentum to model collisions in one dimension.
  • How to use Newton’s experimental law to model inelastic collisions in one dimension.
  • How to calculate the work done by a force and the work done against a resistive force.
  • How to calculate gravitational potential energy and kinetic energy.
  • How to calculate elastic potential energy.
  • How to solve problems in which energy is conserved.
  • How to solve problems in which some energy is lost through work against a dissipative force.
  • How to calculate power and solve problems involving power.
  • How to model elastic collision between bodies in two dimensions.
  • How to model inelastic collision between two bodies in two dimensions.
  • How to calculate the energy lost in a collision.
  • How to calculate probability for a Poisson distribution.
  • How to use the properties of a Poisson distribution.
  • How to use a Poisson distribution to model a binomial distribution.
  • How to use a hypothesis test to test for the mean of a Poisson distribution.
  • How to estimate a population mean from sample data.
  • How to estimating population variance using the sample variance. How to calculate and interpret the standard error of the mean.
  • How and when to apply the Central Limit Theorem to the distribution of sample means.
  • How to use the Central Limit Theorem in probability calculations, using a continuity correction where appropriate.
  • How to apply the Central Limit Theorem to the sum of n identically distributed independent random variables.
  • How to conduct a chi-squared test with the appropriate number of degrees of freedom to test for independence in a contingency table and interpret the results of such a test.
  • How to fit a theoretical distribution, as prescribed by a given hypothesis involving a given ratio, proportion or discrete uniform distribution, to given data.
  • How to use a chi-squared test with the appropriate number of degrees of freedom to carry out a goodness of fit test.
  • How to calculate the probability of making a Type I error from tests based on a Poisson or Binomial distribution.
  • How to calculate probability of making Type I error from tests based on a normal distribution.
  • How to calculate P(Type II error) and power for a hypothesis test for tests based on a normal, Binomial or a Poisson distribution (or any other A level distribution).

Training Course Content

Syllabus

Module 1: Applications of Differential Equations

  • Using differential equations in modelling in kinematics and in other contexts.
  • Hooke’s law.
  • Simple harmonic motion (SHM).
  • Damped oscillatory motion.
  • Light, critical and heavy damping.
  • Coupled differential equations.
Module 2: Momentum and Impulse
  • Momentum and the principle of conservation of momentum.
  • Newton’s experimental law (restitution)
  • Impulse for variable forces.
  • Module 3: Work, Energy and Power
  • The work-energy principle.
  • Conservation of mechanical energy.
  • Gravitational potential energy and kinetic energy.
  • Elastic potential energy.
  • Conservative and dissipative forces.
  • Power
Module 4: Oblique Impact
  • Modelling elastic collision in two dimensions.
  • Modelling inelastic collision in two dimensions.
  • The kinetic energy lost in a collision.
Module 5: Expectation and Variance and the Poisson Distribution
  • The Poisson distribution.
  • Properties of the Poisson distribution.
  • Approximating the binomial distribution.
  • Testing for the mean of a Poisson distribution.
Module 6: The Central Limit Theorem
  • The distribution of a sample mean.
  • Underlying normal distributions.
  • The Central Limit Theorem.
Module 7: Chi-Squared Tests
  • Chi-squared tests and contingency tables.
  • Fitting a theoretical distribution.
  • Testing for goodness of fit.
Module 8: Type I and Type II Errors
  • What are type I and type II errors?
  • A summary of all probability distributions encountered in A level maths and further maths.

Course delivery details

This course is offered through Imperial College London, a partner institute of EdX.

2-4 hours per week

Expenses

  • Verified Track -$49
  • Audit Track - Free
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