糖心Vlog

This module will allow you to build your knowledge of differentiation and integration, how you can solve first and second order differential equations, Taylor Series and more.

Matrices and complex numbers are two fundamental concepts which arise throughout mathematics. In this module you will be introduced to these objects and learn fundamental techniques for working with them in a variety of contexts.

In this module you will learn the fundamentals of probability and statistics, including axioms and combinatorial analysis, distributions, and independence conditions. You will learn how to apply the addition rule of probability and construct diagrams to visually represent data sets. The course also covers the use of descriptive statistics to analyse data and provides hands-on experience with the R software package.

Introduction to Finance is designed to give you an introduction to the wider finance subject area ass well as firm foundation for further studies in finance. You鈥檒l gain a overview of the financial system, instruments and markets, and ideas about finance concepts and problems. The topics covered include investment companies, return and risk, and behavioural finance. You鈥檒l develop and be able to transmit knowledge about the financial system, instruments and markets and ideas about finance concepts and problems at an introductory level; be aware of, at an introductory level, different ways of thinking about and analysing financial phenomena; and, reflecting the principles of how we approach Finance at 糖心Vlog Business School, you鈥檒l gain an appreciation of the role that finance plays in society as whole.

This module introduces programming skills and their applications in a range of mathematical contexts. Mathematical modelling skills will be an important focus, along with structuring and implementing code in MATLAB and R. To help you consolidate these skills, a key part of the module will be investigative computational modelling studies.

This module will provide you with a foundation of knowledge on the mathematics of sets and relations. You will develop an appreciation of mathematical proof techniques, including proof by induction.

This module will introduce you to the underlying principles and basic concepts of programming with the R language. It will cover a wide range of analytics, provide practical experience of powerful R tools, and present real-world examples of how data and analytics are used to gain insights and to improve a business or industry. These examples include string processing, text analytics, and sentiment analysis. Throughout these examples, and many more, we will teach programming techniques that will enable you to apply advanced data science approaches to real-world applications. This module assumes no prior programming skills.

What skills do you need to succeed during your studies? What about after university? How will you harness your knowledge and soft skills to realise your career goals? This module helps you take an active role in developing transferrable skills and capitalising on your unique background. As well as broad reflection on your professional development, this module will help you explore different career directions and prepare you for the application process, supported by an advisor from within the department.

This module continues your journey into probability and statistics. Topics include distribution theory, estimation and Maximum Likelihood estimators, hypothesis testing, basic linear regression and multiple linear regression. You will continue to develop your skills with implementations in R.

Linear systems are some of the most widely-applied concepts in modern algebra. Beginning with the abstract axiomatic definitions of vectors, vector spaces and linear maps, this module allows you to derive powerful methods for understanding many different systems in mathematics and science.

What are the principles of actuarial modelling? And what are survival models? Examine how calculations in clinical trials, pensions, and life and health insurance require reliable estimates of transition intensities/survival rates. Learn how to estimate these intensities. Build your understanding of estimation procedures for lifetime distributions.

How do we rigorously discuss notions of infinity and the infinitely small? When do limits and derivatives of functions make sense? This module introduces the mathematics underlying modern calculus. Fundamental theorems are proved about sets, sequences and series of real numbers, and about continuous and differentiable functions of a single real variable.

Are you able to solve a small linear programming problem using an appropriate version of the Simplex Algorithm? Learn to formulate an appropriate linear programming model and use the MATLAB computer package to solve linear programming problems. Understand the methods of linear programming, including both theoretical and computational aspects.

Ordinary differential equations are the backbone of much applied mathematics, arising everywhere that a physical, financial or other system changes continuously. This module introduces techniques for studying classes of linear and nonlinear differential equations, and for interpreting their solutions.

What skills do you need to succeed during your studies? What about after university? How will you harness your knowledge and soft skills to realise your career goals? This module helps you take an active role in developing transferrable skills and capitalising on your unique background. As well as broad reflection on your professional development, this module will help you explore different career directions and prepare you for the application process, supported by an advisor from within the department.

This module will enable you to expand your knowledge on multiple statistical methods. You will learn the concepts of decision theory and how to apply them, have the chance to explore Monte Carlo simulation, and develop an understanding of Bayesian inference, and the basic concepts of a generalised linear model.

In this module, you will study three application areas of statistics - multivariate methods, demography and epidemiology, and sampling, and how to apply and assess these methods in a variety of situations.

Can you calculate confidence intervals for parameters and prediction intervals for future observations? Represent a linear model in matrix form? Or adapt a model to fit growth curves? Learn to apply linear models to analyse data. Discuss underlying assumptions and standard approaches. Understand methods to design and analyse experiments.

This module focuses on Bayesian and computational statistics. You will develop your understanding of Bayes鈥� theorem and Bayesian statistical modelling, and Markov chain Monte Carlo simulation, by developing algorithms for simple probability distributions.

Ever considered becoming an Actuary? This module covers the required material for the Institute and Faculty of Actuaries CT4 and CT6 syllabus. It explores the stochastic process and principles of actuarial modelling alongside time series models and analysis.

In a world increasingly driven by data, the need for analysis and visualisation is more important than ever. In this module you will look at data through the eyes of a numerical detective. You will work on the lost art of exploratory data analysis, reviewing appropriate methods for data summaries with the aim to summarise, understand, extract hidden patterns and identify relationships. You will then work on graphical data analysis, using simple graphs to understand the data, but also advanced complex methods to scrutinise data and interactive plots to communicate data information to a wider audience. For data analysis and visualisations you will use R-studio, and a combination of R-shiny applications and google visualisations for interactive plotting.

What skills do you need to succeed during your studies? What about after university? How will you harness your knowledge and soft skills to realise your career goals? This module helps you take an active role in developing transferrable skills and capitalising on your unique background. As well as broad reflection on your professional development, this module will help you explore different career directions and prepare you for the application process, supported by an advisor from within the department.