# 2020/2021

## Content, progress and pedagogy of the module

### Learning objectives

#### Knowledge

• Have knowledge about fundamental concepts in probability, including conditional probability and independence
• Have knowledge about discrete and continuous random variables and relevant properties of these
• Have knowledge about various examples of descriptive statistics and graphics, e.g. histograms, boxplots, scatterplots, lag plots and auto covariance plots
• Have knowledge about statistical inference, including estimation, confidence intervals and hypothesis testing
• Have knowledge about basic concepts related to stochastic processes such as stationarity, correlation function and spectral density
• Have elementary knowledge about wiener processes, white noise and linear stochastic differential equations
• Have comprehension of a concrete example of a model for a simple stochastic process

#### Skills

• Be able, given specific data, to specify a relevant statistical model and account for the assumptions and limitations of the chosen model
• Be able to use relevant software for carrying out the statistical analysis of given data and be able to interpret the results of the analysis
• Be able to use statistical models, like linear regression (simple and multiple) and analysis of variance

#### Competences

• Be able to judge the applicability of statistics within own area
• Be capable of performing a critical evaluation of the results of a statistical analysis
• Be capable of communicating the results of a statistical analysis to people with no or little background within statistics.

### Type of instruction

Lectures in combination with practical exercises and self-study, e-learning or similar.

### Extent and expected workload

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student.

## Exam

### Exams

 Name of exam Probability Theory, Stochastic Processes and Applied Statistics Type of exam Written or oral exam ECTS 5 Assessment 7-point grading scale Type of grading Internal examination Criteria of assessment The criteria of assessment are stated in the Examination Policies and Procedures

## Facts about the module

 Danish title Sandsynlighedsregning, stokastiske processer og anvendt statistik Module code N-EE-K1-12A Module type Course Duration 1 semester Semester Autumn ECTS 5 Language of instruction English Empty-place Scheme Yes Location of the lecture Campus Aalborg, Campus Esbjerg Responsible for the module Ege Rubak

## Organisation

 Study Board Study Board of Energy Department Department of Energy Technology Faculty Faculty of Engineering and Science