ENE701 Applied Statistics Course for Engineering

The course is connected to the following study programs

• PhD Programme in Engineering and Science

Course contents

Enable the participants to perform statistical analysis of their own data and to relate the results to practical applications, performing statistical analyses with statistics software. We will follow the theory with practical implementations in the statistical package R, preferably using the students’ own data when possible.

We will start with basic statistical methods and ideas such as condensing the data into statistics and presenting it. Further, we will refresh basic concepts of probability. The statistical concepts and methods will be understood through interpretation of practical application. A mix of bayesian and frequentist concepts and techniques for optimal learning and ability to apply statistical methods with ease and understanding.

Specific content is statistical inference, estimates and hypothesis tests. We will analyse mean and variance from a Gaussian process, proportions, and waiting times from Poisson processes. We will also look at simple and multiple linear regression, and logistics regression.

We will look at test planning, and at interpreting and concluding from the results of a test. There will be a practical project based on the participants' own data consisting of planning, performing and presenting a statistical analysis. This project will form part of the basis for an oral exam.

Teaching methods

Lectures, exercises, project

Assessment methods and criteria

Project + Oral examination. Pass/Fail