Statistical methods have proven enormously valuable in helping scientists interpret the results of their experiments. This is a course about how statisticians draw conclusions from experimental data. Its primary goal is to introduce the student to an important type of reasoning that statisticians call 'inference'. Rather than provide a superficial introduction to a wide variety of inferential methods, we will concentrate on fundamental concepts and study a few of them in depth, while encourage students to think critically about how to apply statistical inference methods in data. Statistical inference rests on the mathematical foundation of probability. Students having taken an introductory course in probability will benefit most from this course. Many statistical procedures rely on softwares for their implementation. This is done through the elegant MATLAB, a software favoured by engineers, mathematicians as well as scientists. Other software like R may also be used.