Text

Statistisk analys i industriella system

  • Högskolepoäng 2.5 hp
  • Studieort Ortsoberoende
  • $stringTranslations.StartDate 2020-10-05 - 2020-12-13 (deltid 17%)
  • Utbildningsnivå Avancerad nivå
  • Kurskod DVA477
  • Huvudområde Datavetenskap

In this course you will learn state-of-the-art statistical modelling for the purpose of analysing industrial data. The course also presents the basics of relational databases and data manipulation techniques needed to prepare the data for analysis.

About this course

In this course you will learn state-of-the-art statistical modelling for the purpose of analysing industrial data. The course first presents the basics of relational databases and data manipulation techniques needed to prepare the data for analysis.An overview of the most popular statistical tools will be given. We will focus on the most powerful tool for the statistical data analysis called R, where you will learn how to use regression and ANOVA models for industrial data. Elements of probability theory and mathematical statistics will be provided as needed.

Modern industrial plants and environments measure and store all relevant production variables. In addition to observation, the data can be obtained also by experimentation.

The course provides fundamental elements of applied statistical analysis that can be used to analyse and model the data obtained from industrial plants, as well as elements of probability theory and mathematical statistics needed for a deeper understanding of methods and a reliable interpretation of the analysis’ results.

Entry requirements

  • 90 credits of which at least 60 credits in one or several of the subjects: Computer science, Electrical engineering, Electronics, including at least 7.5 credits in computer programming, and 7.5 credits in Single Variable Calculus.
  • The mathematics shall include knowledge of elementary calculus: integrals, derivations, series, and sums.
  • In addition English course A/English course 6 is required.

You can also apply for the course and get your eligibility evaluated based on knowledge acquired in other ways, such as work experience, other studies etc.

Course title in Swedish

Statistisk analys i industriella system

Language

English

Teacher

Universitetslektor

Ivan Tomasic

+4621101555

ivan.tomasic@mdh.se

Kursplan

Du kan läsa i detalj om utbildningen, dess innehåll och litteratur m.m. i kursplanen

Se kursplan

Apply to the course

Statistical Analysis in Industrial Systems

Go to application

Application information

After submitting your electronic application, the next step is to submit documentation to demonstrate your eligibility for the course you have applied for. In order to document your eligibility, you must provide your high school diploma and university transcript and proof of your English language proficiency.

Entry requirements

To meet the entry requirements for this course you need to have previous academic qualifications (university studies). You will find the specific entry requirements above.

No academic qualifications?

If you do not have the formal academic qualifications needed for a specific course, you can apply for the course and get your eligibility evaluated based on knowledge acquired in other ways, such as work experience, other studies etc. This is also known as a validation of prior learning.

Recognition of prior learning means the mapping out and assessment of an individual's competence and qualifications, regardless how, where or when they were acquired – in the formal education system or in some other way in Sweden or abroad, just recently or a long time ago.

If you think your knowledge and competences will qualify you for this course, you will need to upload th following with your application:

  • CV with description of your educational and professional background. Your CV must describe your knowledge and competences in relation to the entry requirements.
  • If you refer to work experience, you need to upload an Employers certificate.

If we need more information, we will contact you.

FutureE

The courses are part of the FutureE project where MDH offers online courses in the areas of AI, Environmental and Energy Engineering, Software and Computer Systems Engineering.

For companies that want to collaborate on competence development