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Blekinge Institute of Technology
Department of Mathematics and Natural Science

Revision: 2
Reg.no:


Course syllabus

Mathematical statistics with software

Mathematical statistics with software

6 credits (6 högskolepoäng)

Course code: MS1417
Main field of study: The course is not included in any main field of study at BTH
Subject: Mathematics statistics
Disciplinary domain: Natural sciences
Education level: First-cycle
Specialization: G1F - First cycle, has less than 60 credits in first-cycle course/s as entry requirements

Language of instruction: English
Applies from: 2025-03-11
Approved: 2025-03-11

1. Descision

This course is established by Dean 2023-09-25. The course syllabus is approved by Head of Department of Mathematics and Natural Science 2025-03-11 and applies from 2025-03-11.

2. Entry requirements

Admission to the course requires 2 completed credits in Linear Algebra and 6 completed credits in Calculus in One Variable.

3. Objective and content

3.1 Objective

The course aims to provide students with a deep understanding of probability and statistical theory with applications in technology and economics. The focus is on probability theory as a foundation for further studies in technical fields such as signal processing and telecommunications. An essential part of the course involves learning how to handle statistics effectively with the support of software, enabling students to apply theoretical concepts to real-world data.

3.2 Content

  • Combinatorics
  • Probability theory
  • Conditional probability and Bayes’ theorem
  • Discrete and continuous random variables in one dimension
  • Overview of independence
  • Various distributions, particularly Poisson, binomial, exponential, and normal distributions, including approximations
  • Expectation, variance, standard deviation, covariance, correlation
  • Point estimation, including the maximum likelihood (ML) method
  • Interval estimation
  • Hypothesis testing
  • Simple linear regression
  • Applications, primarily from various technical fields

4. Learning outcomes

The following learning outcomes are examined in the course:

4.1. Knowledge and understanding

On completion of the course, the student will be able to:

  • Develop a comprehensive understanding of probability and statistical theory.
  • Gain proficiency in fundamental probability concepts with applications in technical fields and economics.
  • Master statistical methods for point estimation, interval estimation, and hypothesis testing.
  • Understand and apply linear regression techniques.
  • Understand the foundational role of probability and statistics in fields like signal processing and telecommunications.

4.2. Competence and skills

On completion of the course, the student will be able to:

  • Analyze and synthesize complex statistical data, drawing insights and identifying patterns to inform decision-making.

4.3. Judgement and approach

On completion of the course, the student will be able to:

  • Interpret and derive meaningful conclusions from statistical data.
  • Critically evaluate the statistical analyses performed by others, assessing the validity of their methods and the implications of their conclusions.

5. Learning activities

The course is delivered through lectures, exercises, and computer labs. Instruction is generally conducted in English. However, instruction in Swedish may be provided if the course instructor deems it necessary.

6. Assessment and grading

Modes of examinations of the course

Code Module Credit Grade
2510 On-campus Examination[1] 4 credits AF
2520 Written assignment 2 credits GU

[1] Determines the final grade for the course, which will only be issued when all components have been approved.

The course will be graded A Excellent, B Very good, C Good, D Satisfactory, E Sufficient, FX Failed result, a little more work required, F Fail.

The examiner may carry out oral follow-up of written examinations.

The information before the start of the course states the assessment criteria and make explicit in which modes of examination that the learning outcomes are assessed.

An examiner can, after consulting the Disability Advisor at BTH, decide on a customized examination form for a student with a long-term disability to be provided with an examination equivalent to one given to a student who is not disabled.

7. Course evaluation

The course evaluation should be carried out in line with BTH:s course evaluation template and process.

8. Restrictions regarding degree

The course can form part of a degree but not together with another course the content of which completely or partly corresponds with the contents of this course.

9. Course literature and other materials of instruction

Walpole, R.E., Myers, R.H., Myers, S.L. & Ye, K. (2012 or later). Probability and Statistics for engineers and scientists. 9:th edition or later. Pearson (ISBN 978-0-321-62911-1)

10. Additional information

This course replaces MS1413

This is not a legal document. If you would like a copy of the legal decision regarding this course plan, contact the registrar at Blekinge Institute of Technology.