Statistics with Applications

Descriptive statistics. Probability calculations, including probability laws, conditional probability and independence, random variables, discrete and continuous probability distributions, expected value, variance, bivariate probability distributions, covariance and correlation. Estimation, confidence intervals and hypothesis testing. The central limit theorem. Introduction to simple linear regression.

1. Knowledge. The student knows basic concepts in probability, simple probability models and statistical inference. In addition, the student knows a number of basic statistical methods and the assumptions underlying these methods. 2. Skills. The student is able to use his or her knowledge in recognising and analysing simple forms of data in the natural sciences. In addition, the student is able to communicate with statisticians about analysis of data arising in more complex situations.

Lectures and compulsory exercises. Written final examination is the basis for the grade awarded in the course. Parts of this course can be taught in English.