Course Syllabus for

Design of Experiments
Försöksplanering

FMSF65F, 7.5 credits

Valid from: Autumn 2020
Decided by: Professor Thomas Johansson
Date of establishment: 2020-08-26

General Information

Division: Mathematical Statistics
Course type: Course given jointly for second and third cycle
The course is also given at second-cycle level with course code: FMSF65
Teaching language: English

Aim

This is a basic course in designing experiments and analyzing the resulting data. It is intended for engineers, physical/chemical scientists and scientists from other fields such as biotechnology and biology. The course deals with the types of experiments that are frequently conducted in industrial settings. Its objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Opportunities to use the principles taught in the course arise in all phases of engineering and scientific work, including technology development, new product design and development, process development, and manufacturing process improvement. Applications from various fields of engineering (including chemical, mechanical, electrical, materials science, industrial, etc.) will be illustrated throughout the course.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Course Contents

Simple design with fixed and random effects. Simultaneous confidence intervals. Requirements for analysis of variance: transformations, model validation, residual analysis. Factorial design with fixed, random, and mixed effects. Additivity and interaction. Complete and incomplete designs. Randomised block designs, Latin squares and confounding. Regression and analysis of covariance.

Course Literature

Instruction Details

Types of instruction: Lectures, laboratory exercises, exercises, project

Examination Details

Examination formats: Written exam, written report
Grading scale: Failed, pass
Examiner:

Admission Details

Assumed prior knowledge: Basic mathematical statistics knowledge and programming experience.

Course Occasion Information

Contact and Other Information

Course coordinators:
Web page: www.maths.lth.se/matstat/kurser/fmsf65/


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