ØAMET1100 Statistics Course description

OPPDATERT PENSUMLISTE FINNER DU I "OM EMNET" (IKKE NEDERST I EMNEBESKRIVELSEN).

Studenten tilegner seg her det nødvendige grunnlaget i sannsynlighetsregning og statistikk for andre emner i studiet. Studenten skal få analytisk innsikt, og det legges vekt på å vise anvendelser av sannsynlighetsregning og statistisk metode innen et bredt spekter av problemstillinger knyttet til det økonomisk-administrative fagområdet.

Two internal examiners. External examiner is used periodically. The exam grade can be appealed.

Ingen forkunnskapskrav.

Kunnskaper

Studenten har

• grunnleggende kunnskap innen sannsynlighetsregning og statistikk slik det anvendes i økonomisk-administrative fag.

Ferdigheter

Studenten kan

• presentere og tolke statistiske data ved hjelp av sentral- og spredningsmål, frekvensfordelinger og grafiske metoder
• grunnleggende sannsynlighetsregning inkludert sannsynlighetsmodeller, kombinatorikk, utvalgsmodeller, betingede sannsynligheter, lov om total sannsynlighet, Bayes lov og uavhengighet
• analysere sannsynlighetsfordelinger og beregne forventning og varians til en stokastisk variabel og til lineærkombinasjoner av stokastiske variable.
• forstå simultane sannsynlighetsfordelinger inkludert beregning av forventning, varians og kovarians
• velge sannsynlighetsmodell og regne med diskrete og kontinuerlige sannsynlighetsfordelinger, inkludert Binomisk fordeling, Hypergeometrisk fordeling, Poissonfordeling, Normalfordeling/Normaltilnærming og t-fordeling
• estimere ukjente parametre, både punktestimering og intervallestimering
• foreta hypotesetesting i målemodell og binomisk modell og vurdere ulike testmetoder; tolke signifikansnivå, signifikanssannsynlighet og teststyrke
• anvende og tolke regresjonsanalyse, herunder estimering og hypotesetest av regresjonskoeffisienten og prediksjon
• beregne og tolke korrelasjonskoeffisienten
• foreta kjikvadrattester, både modelltesting og test av uavhengighet

Generell kompetanse

Studenten kan

• forholde seg til og operasjonalisere usikkerhet.

This course has a focus on the practices and technologies used for network-based services such as large web sites and backend systems. It provides topics specific to large architectures, such as: containers, service architectures, load balancing and service continuity. In addition, topics which are relevant for working with software projects often found in this context are covered, such as release management, automated testing and agile development principles.

No formal requirements over and above the admission requirements.

The student should have the following outcomes upon completing the course:

Knowledge

Upon successful completion of the course, the student will:

• have advanced knowledge of service architectures and how they are applied in the industry
• have advanced knowledge of the techniques and methods used to build large-scale network-based services
• have a deep understanding of the principle of service continuity and the techniques and methods used to make services robust to infrastructure failure
• have a deep understanding of agile development methodologies and how they apply to system administration
• have expert insight into release management from an operations perspective

Skills

Upon successful completion of the course, the student:

• can evaluate and discuss a service architecture in relationship with the intended service function with regard to performance, scale and robustness
• can apply load balancing and failover techniques in order to create robust network-based services
• can define release-management strategies
• can evaluate and discuss a release-management plan in relationship to an agile development project

General competence

Upon successful completion of the course, the student:

• can analyze release management in the industry
• can communicate challenges, analysis and conclusions in developer operations with regard to service architectures and release management to specialists as well as the general public

The following required coursework must be approved before the student can take the exam:

Three online questionaires addressing their progress and reflections. Each questionnaire should take between 10 and 15 minutes to complete.

The students will work individually to complete three tasks of which two are of a technical nature and one an essay. The results are documented in a portfolio as two technical reports and one essay. The total amount of text should be about 60 +/- 10 pages, not including appendix with scripts etc.

The portfolio will be graded as a whole, with the following guideline for the relative weight of the different documents:

• Technical report 1: 40%
• Technical report 2: 40%
• Essay: 20%

All exams must be passed in order to pass the course.

For the final assessment a grading scale from A to E is used, where A denotes the highest and E the lowest pass grade, and F denotes a fail.