Mathematical statistics: Data Analysis, Statistical Learning and Visualization with Project

Education facts

Code: MASC06

<p>The overarching goal of the course is to give an overview of basic data wrangling and visualization, focusing on the ability to identify and illustrate important features of a data set.</p><p>Basic methods for data handling and common visualisation methods for data. Methods for unsupervised and supervised learning such as: clustering; hierarchical clustering; and regression and decision tree methods for classification and regression problems. Methods for model selection and validation such as: bootstrap, split of data into training and test, and cross-validation.</p><p>https://www.maths.lu.se/english/education/all-courses/courses-faculty-of-science/</p>

Entry requirements

For admission to the course, general entry requirements and 60 ECTS credits in Science, Technology, Engineering and/or Mathematics including knowledge equivalent to at least on of the flollowing courses: MASA03 Mathematical statistics: Basic course, 15 ECTS, MASB13 Mathematical Statistics for Physicists 7.5 ECTS, MASB02 Mathematical Statistics for Chemists 7.5 ECTS. English course 6/B.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Mathematical statistics: Data Analysis, Statistical Learning and Visualization with Project

  Lund University

  Start date: 19 January 2026

  End date: 22 March 2026

  Pace of study: 50 %