MET 1190 Statistics

APPLIES TO ACADEMIC YEAR 2014/2015

MET 1190 Statistics


Responsible for the course
Christian Brinch

Department
Department of Economics

Term
According to study plan

ECTS Credits
7,5

Language of instruction
Norwegian

Introduction
The use of abstract mathematical and statistical models to describe and analyze a complex reality has in many areas proved useful. In this course students are introduced to useful and well established methods that are applicable in practice.


Learning outcome
After completing the learning process described in this course description, students will:

Aquried Knowledge
Based on a through understanding of concepts and notions in probability and statistics, the students will understand that statistical techniques and methods are based on assumptions and requirements.

Aquired Skills

  • be able to handle and analyze quantitative uncertainty and probability
  • be able to model using discrete and continuous stochastic variables, and be capable in handling, analyzing and presenting data related to these with and without using computerized tools
  • be able to handle the sample of a population and be capable in methods for statistical inference
  • be able to select correct model and test in different situations and be able to conclude from these
  • be able to compute with probabilities
  • be able to estimate a simple regression model

Reflection
  • On completion of the course the students will have developed a critical attitude towards results and the validity of statistical analysis.

Prerequisites
Basic skills in mathematics and statistics equivalent to admission requirements for the program.

Compulsory reading
Books:
Løvås, Gunnar G. 2013. Statistikk for universiteter og høyskoler. 3. utg. Universitetsforlaget. kap 1-7

Recommended reading

Course outline
  1. Descriptive statistics
  2. Stochastic experiments and stochastic variables
  3. Computation with probabilities, elementary set theory
  4. Discrete probability distributions
  5. Continuous probability distributions
  6. Inference for parameters in discrete probability distributions
  7. Inference for parameters in continuous probability distributions
  8. Estimation
  9. Hypothesis testing
  10. Simple linear regression
  11. Inference in simple linear regression model
  12. Selection of model and methods

Computer-based tools
Excel.

Learning process and workload
To each lecture there will be exercises and reading assignments. The student must gain knowledge from the material presented in the reading assignments and work through the exercises. Some of the exercises must be solved using Excel. The exam will require that the student has solved the exercises during the semester. Feedback will be given by sample solutions and presentations.

Workload for the student:
Activity
Use of hours
Lectures
54
Work with exercises (and computer-base tools)
96
Reading assignments
40
Preparation for final exam
10
Recommended use of time
200


    Examination
    A five hour individual exam, concludes the course.

    Examination code(s)
    MET 11901 - Written exam, counts 100% towards the final grade in MET 1190 Statistics, 7,5 credits.

    Examination support materials
    All aids + calculator TEXAS INSTRUMENTS BA II Plus™ are allowed.
    Students are encouraged to bring solutions to assignments that has been given trough the semester.
    Examination support materials at written examiniations are explained under examination information in the student portal @BI. Please note use of calculator and dictionary. https://at.bi.no/EN/Pages/Exa_Hjelpemidler-til-eksamen.aspx


    Re-sit examination
    Re-sit examination is offered every term.

    Additional information