Mathematical statistics (Bygg Hbg)
Official Course Description
The course contains fundamental concepts in probability theory, inference theory, and regression analysis.
In probability theory the concepts used are random variables and distributions for describing variation and random phenomena, often related to engineering applications. Different distributions, such as binomial, Poisson, normal, exponential, and log normal distributions, are studied and the concept of expectation and variance of a distribution is introduced. Special attention is paid to the normal distribution and its property as a limit distribution.
In inference theory we start with observed data and estimate parameters in simple probability models, and describe the uncertainty of the estimates. Emphasis is placed on the relationship between the model and the reality based problem, as well as the conclusions that can be drawn from observed data. In this analysis we use basic techniques, such as confidence intervals and hypothesis testing. Examples of applications are given.
In regression analysis we study how the relationship between two or more variables can be described. Most often the relationship will be linear.