This course introduces the basic techniques of demographic analysis. Students will become familiar with the sources  of data available for demographic research. Population composition and change measures will be presented. Measures of mortality, fertility, marriage and migration levels and patterns will be defined. Life table, standardization  and population projection techniques will also be explored.

This module is not Computational Statistics (statistical methods that use computation). Rather it is an introduction to “Programming”. The module's aim is to introduce to students software  such as MATLAB, R, Python, etc.. ,programming in order to implement numerical methods to solve problems in applied mathematics and statistics.

References

MATLAB

1).  Amos Gilat, MATLAB: An introduction with Applications. John & Sons, Inc., Sixth Edition, 2017.

2. Steven Chapra, Applied Numerical Methods with MATLAB for Engineers and Scientists.

R

1).  Robert I. Kabacoff, R in Action Data analysis and graphics with R. Second edition, 2015.
2).  Basics 

An Introduction to R: Notes on R: A Programming Environment for Data Analysis and Graphics by W. N. Variables, D. M. Smith and the R Development Core Team.

  Course's aim

The aim of this module is to provide the students  with deeper knowledge of linear algebra for the use in later courses and in Engineering and  mathematical-Physics  problems. It deals with linear maps between finite dimensional vector spaces, their representations and their applications. The course is made of four main chapters: Endomorphisms, Euclidian spaces, Unitary spaces and Jordan forms. Each chapter contains a series of exercises and at the end of two chapters an assignment is provided.

The aims of this module is to introduce to the students the basics of probability theory that are necessary to understand statistical inference. Topics covered are counting techniques, basic concepts of probability, conditional probability, random variables, probability distributions, joint and marginal distributions, conditional distributions, expectations, and moment generating function

The module named Calculus 2 is the continuation of the module called Calculus 1, done in the first trimestre of the academic year. Calculus 1 deals with functions of single real variable, it is also called "Single real variable". Its main parts are Differential calculus and Integral calculus. However, Calculus 2 deals with functions of several variables, it is also called for that reason, "Multivariate calculus". Its main parts are - Partial Derivatives - Multiple Integrals and Vector Calculus.

The module target students for first year -Applied Mathematics, - Mathematical Statistics and Physics.

Welcome to the Complex Analysis Module

This course will introduce the students in applying Complex Analysis to model Engineering and Physics problems. the course start by generalities on complex analysis (Complex numbers, complex differentiation and integration) , secondary the Comformal mapping are introduced and we shall end the course by devoloping  the potential theory which is very important to Scientists and Engineers.

Uwimbabazi Ruganzu Leon Fidele(PhD), Email: ruganzu01@gmail.com, Tel: 0784878618.