Course

Probability and Statistics 1 (STA100)

The course gives an introduction to basic probability theory, including an introduction to common discrete and continuous probability models, and an introduction to simulation. Further the course gives an introduction to descriptive statistics and statistical analyses, in particular estimation and confidence intervals, hypothesis testing and regression analysis. An integrated part of the course is an introduction to R for programming, data analysis and simulation.


Dette er emnebeskrivelsen for studieåret 2025-2026

Fakta

Emnekode

STA100

Vekting (stp)

10

Semester undervisningsstart

Spring

Undervisningsspråk

Norwegian

Antall semestre

1

Vurderingssemester

Spring

Content

The course gives an introduction to descriptive statistics and basic probability theory for discrete and continuous probability models. Introductory theory for estimation and for statistical hypothesis testing in the most common situations is presented. Emphasis is made on both theoretical understanding and applications. An introduction to simulation is also given. An introduction to use of R for data analysis, programming and simulation is an integrated part of the course.

Topics covered: Introduction to basic probability theory, included conditional probability, expectation, variance and the most common probability distributions like binomial, hypergeometric, poisson, exponential and normal. Introduction to simulation. An introduction to point estimation, confidence intervals and hypothesis testing in one and two sample situations. An introduction to correlation, regression analysis, analysis of variance and chi-squared tests. Use of R for data analysis, programming and simulation.

Learning outcome

After having completed the course the student should:

  • Be able to use basic methods for analysis and presentation of data.
  • Be able to do basic probability calculations.
  • Know what a random variable, probability distribution, expectation and variance is.
  • Be able to calculate expectation, variance and probabilities for random variables and simple functions of random variables.
  • Be able to use basic probability distributions like binomial, poission, hypergeometric, exponential and normal.
  • Be able to use the central limit theorem.
  • Be able to set up, run and interpret the result of simple simulation models.
  • Be able to find estimators and calculate confidence intervals for some important parameters in probability distributions.
  • Have a basic understanding of hypothesis testing and be able to perform hypothesis testing for one and several samples.
  • Know the theory for, and be able to use correlation, regression analysis and simple analysis of variance.
  • Know the assumptions for the various methods and be able to judge whether the assumptions are fulfilled.
  • Be able to use chi square tests
  • Be able to use some R for basic data analysis, programming and simulation.

Forkunnskapskrav

Mathematical methods 1 (ÅMA100)

Anbefalte forkunnskaper

Mathematical Methods 1 (MAT100)

Exam

Form of assessment Weight Duration Marks Aid
Written exam 1/1 4 Hours Letter grades Basic calculator


Written exam is with pen and paper

Vilkår for å gå opp til eksamen/vurdering

Six compulsory assignments

Compulsory exercises have to be approved in order to take an examination.

Mandatory work demands (such as hand in assignments, lab- assignments, projects, etc) must be approved by subject teacher three weeks ahead of examination date.

Fagperson(er)

Head of Department:

Bjørn Henrik Auestad

Course coordinator:

Jan Terje Kvaløy

Method of work

To to six hours of lectures, two hours of organized problem solving classes and four to eight hours of self study per week.

Overlapping

Emne Reduksjon (SP)
Probability and Statistics 1 (STA100_1) , Introduction to Probability and Statistics (ÅMA110_1) 5

Åpent for

Battery and Energy Engineering - Bachelor in Engineering Biological Chemistry - Biotechnology - Bachelor's Degree Programme Civil Engineering - Bachelor in Engineering Computer Science - Bachelor in Engineering Computer Science - Bachelor in Engineering, Part-Time Electrical Engineering - Bachelor's Degree Programme, part-time Electrical Engineering - Bachelor's Degree Programme Energy and Petroleum Engineering, Vocational Path - Bachelor in Engineering Energy and Petroleum Engineering - Bachelor in Engineering Geosciences and Energy Resources - Bachelor in Engineering Environmental Engineering - Bachelor in Engineering Mechanical Engineering - Bachelor in Engineering Mathematics and Physics - Bachelor's Degree Programme Medical technology - Bachelor in Engineering Medical Technology - Bachelor in Engineering - part time Geosciences Engineering - Bachelor in Engineering Petroleum Technology - Bachelor in Engineering
Admission to Single Courses at the Faculty of Science and Technology
City and Regional Planning - Master of Science Degree Programme, Five Years Environmental Engineering - Master of Science Degree Programme Industrial Economics - Master of Science Degree Programme Industrial Economics - Master of Science Degree Programme, Five Year Industrial Automation and Signal Processing - Master's Degree Programme - 5 year Robot Technology and Signal Processing - Master's Degree Programme Structural and Mechanical Engineering - Master of Science Degree Programme. Five Years Advanced teacher education for levels 8-13 Advanced teacher education for level 8-13 in science Mathematics and Physics - Five Year Integrated Master's Degree Programme Marine and Subsea Technology, Master of Science Degree Programme, Five Years Offshore Technology - Master's Degree Programme Petroleum Engineering - Master of Science Degree Programme Petroleum Engineering - Master of Science Degree Programme, Five Years Master's Degree Programme in Societal Safety, Specialisation in Technical Social Safety Mathematics - One-Year Programme Science and Technology - one-year programme

Emneevaluering

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.
The course description is retrieved from FS (Felles studentsystem). Version 1