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

• be able to explain and use basic methods in factorial experiments,
• be able to explain and use basic methods in analysis of variance with fixed and random effects, regression and analysis of covariance.

Competences and Skills

For a passing grade the doctoral student must

• be able to plan a factorial experiment,
• be able to suggest an experimental plan suitable for a given problem,
• be able to structure and analyse sets of data using a computer package and critically examine the result,
• be able to, both in written reports and orally at seminars, account for the solutions of statistical problems

## 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

• Box, George E. P., Hunter, J. Stuart & Hunter, W.: Statistics for experimenters: design, innovation, and discovery. Wiley-Blackwell, 2005. ISBN 9780471718130.
• Montgomery, Douglas C.: Design and Analysis of Experiments. 2019. ISBN 9781119492443.

## Instruction Details

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

## Examination Details

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