Statistics (2021)

Course manager

Christian Møller Pedersen 

Semester schedule

Spring (13-week period)



Language of instruction


Course type



Competences corresponding to participation in the course Mathematics 1 is recommended 


Together with Mathematics 1, this course will provide the students with a basic mathematical and statistical foundation for the Bachelor of Engineering in Biotechnology programme. Thus, focus is on mathematical and statistical theories and methods to be applied in connection with other academic disciplines within the programme, including project work. 

The purpose of the course is to provide the students with a general understanding of how statistical concepts, theories and techniques can be applied in connection with the description and analysis of conditions and problems of relevance to the educational programme, and to the engineering profession as such.


  • Simple mathematical models for selected problems
  • Basic descriptive statistics of experimental observations
  • Selected statistical calculation methods for data analysis
  • Calculations of uncertainty
  • Principal Component Analysis (PCA)

Learning targets

On completion of the course, the student is expected to be able to:


  • Understand and explain the application of mathematical models in the description of simple physical/chemical systems
  • Understand and explain simple calculations in the description of data sets, e.g. calculations of uncertainty
  • Understand the principles in hypothesis testing and confidence intervals
  • Understand and explain the principles behind simple and multiple linear regression
  • Understand the principles of PCA



  • Apply selected commercial computer programs for the purposes of mathematical and statistical analysis and calculation
  • Apply statistical calculations and assessments on the basis of e.g.

    • Poisson distribution
    • t-distribution
    • Chi-square distribution
    • Hypothesis tests
    • Confidence intervals

  • The selection and application of statistical data-analysis methods, such as analysis of variance, regression and correlation analysis
  • Calculate uncertainties in the application of calculation formula within experimental measurements
  • Apply probability-based calculations in connection with the description of expected patterns in data materials
  • Apply fundamental statistical concepts and methods based on e.g. the Gaussian distribution


  • Set up quantitative models on the basis of measured data for the estimation of model parameters

Teaching method

Class-bassed teaching, prodcasts and problem solution 

Qualifications for examination participation

  • Approval of all written assignments

Every assignment will be performed and submitted subject to guidelines set out by the course manager.

Examination and aids

Written examination. Duration of examination: 4 hours.

Permitted aids: Textbook, notes and mathematical program/spreadsheet. No access to the internet.

The form of examination at a 3rd attempt may vary from the above. 




The 7-point grading scale