Valid for: 2015/16
Decided by: Education Board B
Date of Decision: 2015-04-16
Compulsory for: BI2
Language of instruction: The course will be given in Swedish
The aim of the course is to give a basic knowledge of statistical concepts in technology, science and economics and to give training in the use of computers for statistical calculations and in the evaluation of the quality of statistical investigations.
The course will give the student knowledge in how to describe random variation and understanding of the principles behind statistical analysis. It will also give the student a tool-box with the most common models and methods and the ability to use these in different practical situations.
The aim is both to give a general knowledge in statistics and to give a foundation for further studies.
The general knowledge is required for those who in their professional activities perhaps will not need to perform statistical analyses regularly, but who will have to interpret results from various investigations, present results and perform simple statistical analyses.
The course will also give a foundation for further studies, foremost by defining and using the basic concepts within probability theory, risk-analysis, decision theory, statistical modelling etc.
Knowledge and understanding
For a passing grade the student must
Competences and skills
For a passing grade the student must
Judgement and approach
For a passing grade the student must
The course presents the theoretical and practical foundations for statistical analysis of data. Concepts as event, probability (risk), independence and expected value are defined. Further, different discrete and continuous probability models are studied, e.g. binomial, poisson and normal models. The structure and basic concepts of decision analysis are studied, e. g. Bayes’ theorem, decision-trees and sensitivity analysis. The foundations of descriptive statistics: Principles of tabulation and graphs, measures of location, variation and association, standardization, and index-theory. The meaning of concepts as statistical precision and statistical significance are discussed. The course will also give an introduction to Monte Carlo simulation.
Grading scale: TH
Assessment: Written examination and approved computer exercises.
Parts
Code: 0195. Name: Statistics with Decision Theory.
Credits: 9. Grading scale: TH.
Code: 0295. Name: Laboratory Work.
Credits: 0. Grading scale: UG.
Required prior knowledge: FMA415 Calculus in one Variable.
The number of participants is limited to: No
Course coordinator: Per-Erik Isberg, per-erik.isberg@stat.lu.se
Course coordinator: Lars Wahlgren , lars.wahlgren@stat.lu.se
Course homepage: http://www.stat.lu.se/dk/tnx071.htm
Further information: For retake of examination, contact the course coordinator.